2017 CONNECTOR

News from the MIT Department of Electrical Engineering and Computer Science CONNECTOR 2017

15 StartMIT: Make It Your Business 60 The Internet of (Play) Things

CONTENTS 1 A Letter from the Department Head FACULTY FOCUS FEATURES 39 Faculty Awards

4 SuperUROP: Bots, Bit Flips, and Catching 45 Faculty Research Innovation Fellowships the Bus (FRIFs)

6 When USAGE Speaks, EECS Listens 46 New EECS Associate Department Heads

8 Helping Technology and Policy Work 47 EECS Professorships Anantha P. Chandrakasan Together: Keertan Kini 51 New Career Development Chairs Department Head 10 The Balancing Act: Alyssa Cartwright 51 New Faculty Nancy Lynch 11 Three from EECS Win Lemelson-MIT Student Prizes 54 Remembering EECS Faculty: Associate Department Head Mildred S. Dresselhaus, Robert Fano 13 EECS Senior Wins ‘Jeopardy’ College Asu Ozdaglar Championship EDUCATION NEWS Associate Department Head 15 StartMIT: Make It Your Business 58 Machine Learning for Just About Everyone Anne Stuart 17 StartMIT’s Innovation Night 60 The Internet of (Play) Things Communications Officer 19 StartMIT: Entrepreneurship in Action – Connector Editor on Two Coasts 63 Talk Science to Me

21 The Engine: Up and Running ALUMNI NEWS Suzana Lisanti Special Projects Manager 23 Masterworks and EECScon: Showcasing 66 Michal Depa: An Innovation ‘Ecosystem’ Connector Photo Editor Students’ Work for Better Health Care RESEARCH UPDATES 68 Dario Gil: On the Cutting Edge of the Connector Production Team Cutting Edge Design by Wing Ngan 26 Michael Carbin: Verifying Application- Specific Fault Tolerance via First-Class 70 Philip Guo: Making Programming Printing by Puritan Capital Fault Models Accessible for All

29 St efanie Mueller: Interacting with 72 Cal Newport: Dual Careers Personal Fabrication Machines Contact 74 Martin F. Schlecht: Life Beyond MIT MIT EECS Connector 32 Devavrat Shah: Social Data Processing 76 77 Massachusetts Avenue Lisa Su: An Industry Leader Returns to 35 Max Shulaker: Next-Generation MIT Room 38-467 Nanosystems Q & A Cambridge, MA, 02139 78 Margaret Guo: Swimming Toward eecs.mit.edu Success [email protected] DONOR RECOGNITION A LETTER FROM THE DEPARTMENT HEAD

Greetings from MIT! This has been an exciting year for EECS as we celebrate our community’s achievements. We’ve developed new courses on in-demand topics, increased opportunities for research and entrepreneurship, and expanded efforts to enhance student and postdoc experiences. Following are several highlights from the past year, all explored in more depth in this publication’s pages.

Undergraduates as Researchers: SuperUROP

SuperUROP is a program designed to provide a more in- depth experience for juniors and seniors who have already completed a traditional undergraduate research opportunity program (UROP) project. Through participation in graduate- level research, and weekly guest lectures from distinguished speakers, the year-long program prepares students for work Anantha Chandrakasan in academia, industry, and start-ups. The 12-credit Seminar in Undergraduate Advanced Research (6.UAR), offered in conjunction with SuperUROP, teaches students valuable Entrepreneurship: StartMIT technical communication skills. Each student is eligible to receive a named stipend that is generously funded by gifts Now in its fourth year, StartMIT is designed to shorten the from industry sources and alumni. In the 2016-2017 academic learning curve for aspiring entrepreneurs, teaching them about year, more than 140 students completed SuperUROP projects. startup culture and ethics, effective team-building, intellectual Launched by EECS in 2012, the SuperUROP is now offered to property issues, value propositions, and more. The program all School of Engineering (SoE) departments. includes an intensive for-credit workshop held during MIT’s winter Independent Activities Period (IAP) and site visits to Ongoing Dialogue Between Students and EECS startups and other companies. Leadership: USAGE This year’s StartMIT students and postdocs heard from nearly The department continues to benefit from the regular input of 70 leading innovators. Students learned to develop and pitch the Undergraduate Student Advisory Group in EECS (USAGE), their ideas, refined their projects in hands-on activities, and which I formed in the 2011-2012 academic year as part of the met with MIT alumni and other entrepreneurs. department’s strategic planning process. I’m grateful to this year’s 30-plus USAGE members, who shared their thoughts During the 2017 spring break, some StartMIT participants on everything from faculty advising to training for teaching traveled to California, where they visited leading San Francisco assistants, met with our biennial Visiting Committee, and and Silicon Valley companies and networked with MIT alumni helped design the recently reopened EECS student lounge. and local professionals. In addition, StartMIT students can leverage the MIT Sandbox Innovation Fund, a program offering tailored educational experiences, mentoring, and seed funding of up to $25,000 for qualified teams.

LEADERSHIP UPDATE Entrepreneurship: The Engine

As this issue of the Connector went to press, Anantha MIT established The Engine, an initiative that combines an Chandrakasan was named Dean of the MIT School accelerator, a network of facilities and experts, and a fund that of Engineering, effective July 1, 2017. Chandrakasan will provide startups with stable financial support and access to succeeded Ian A. Waitz, who became MIT’s vice costly resources. The Engine, which was announced in October chancellor. A new EECS department head is expected 2016, closed its first investment fund of $150 million in April to be named this fall. Asuman Ozdaglar, associate 2017. It will focus on startups that are developing “tough” department head, will serve as interim department technologies — such as robotics, manufacturing, energy, head during the search.For details, visit eecs.mit.edu and biotech — which need time to commercialize. Charged or news.mit.edu. by Provost Martin A. Schmidt, I led several MIT Working Groups focused on the development of Institute policies and procedures related to working with The Engine. Expect to hear much more about this exciting initiative in the coming months and years. eecs.mit.edu 2017 CONNECTOR perspectives 1 Building Communication Skills: Comm6 Initiative for MIT’s 2017 PhD hooding ceremony). I hope you’ll enjoy these accounts of some truly remarkable members of the Effective communication skills are in high demand among EECS community. employers today, so we continue to strengthen our offerings in that area. All EECS students have access to the department’s EECS Leadership Communication Lab, where 10 peer advisors provide free coaching and feedback. Since September 2016, more than 250 Last year, I announced that I would be stepping down as students have visited the lab for assistance with everything department head, but have stayed on at the request of SoE from giving oral presentations to formatting their resumes, and Dean Ian A. Waitz to address some key issues facing the more than 270 have attended workshops on posters, pitches, department. It has been a pleasure serving the department proposals, and other topics. We expect demand to keep over the past year, collaborating with associate department growing here as well. heads Nancy Lynch and Asu Ozdaglar, who succeeded Silvio Micali and David Perreault in those roles. Nancy and Asu have Enhancing the Postdoc Experience: Postdoc6 had a busy year, contributing to the department in many ways, and in particular with the hiring of new faculty. Through our Postdoc6 initiative, we’ve been increasing mentoring and networking opportunities for the postdocs who Diversity in Enrollments work in the four EECS-affiliated labs. Several times annually, we offer two-day offsite workshops to help small groups of EECS enrollments continue to set new records, in terms of both postdocs learn leadership, management, and communication numbers and diversity. A total of 1,270 undergrads enrolled for skills. In collaboration with the four labs, we offer regular Fall 2016 (up from 1,205 the previous year); of these, 39 percent social hours to help postdocs meet their colleagues. Feedback are women and 12 percent identify as under-represented has been extremely positive, and future postdocs will benefit minorities (URMs). Thirty-three percent of this year’s MEng from these offerings as well. students are women. Of the 118 SM/PhD students who joined the department in Fall 2016, 21 percent are women and 5 Education, Research, Faculty News percent identify as URMs. Finally, among 613 total graduate students for 2016-2017, 21 percent are women and 58 percent In this issue, you’ll find articles on several EECS courses hold international citizenship. I’m also pleased to note that, covering high-profile topics such as machine learning, mobile for the fourth consecutive year, our entire entering graduate and sensor computing, and the Internet of Things, along with class received financial assistance via fellowships, research or updates on the department’s new undergraduate curriculum teaching assistantships, or EECS-provided support. and computer science minor. You’ll also find updates from researchers in the four EECS-affiliated labs, introductions to As always, we’re eager to hear from EECS alumni, supporters, new faculty, details on appointments to professorships and and friends, especially in exploring ways for you to share your career-development chairs, and an impressive list of our expertise with current students and faculty. I welcome your faculty’s latest awards, honors, and achievements. input. Please stay in touch directly or through our website and other social-network channels. Sadly, the department lost two giants this past year. The Faculty Focus section includes tributes to Institute Professor Sincerely, Emerita Mildred Dresselhaus, and to communication and computing pioneer Robert Fano, the founding director of Anantha P. Chandrakasan Project MAC, which evolved into today’s Computer Science and Vannevar Bush Professor of Electrical Engineering and Artificial Intelligence Laboratory (CSAIL) at MIT. Computer Science Department Head, MIT Electrical Engineering and EECS Alumni News Computer Science

A special highlight of this issue is the collection of stories about EECS alumni (including Advanced Micro Devices CEO Lisa Su, a three-time alumna, who served as guest speaker

“Effective communication YOUR TURN skills are in high demand We’d love to hear your feedback on and story ideas for the Connector. Which articles did you most enjoy? among employers today, What suggestions do you have for future features or profiles? Would you prefer to read future Connectors in so we continue to strengthen print or online or both? Please send your thoughts to our offerings in that area.” [email protected]. Thank you!

2 perspectives CONNECTOR 2017 eecs.mit.edu FEATURES

SuperUROP: Bots, Bit Flips, and Catching the Bus 4

When USAGE Speaks, EECS Listens 6

Helping Technology and Policy Work Together: Keertan Kini 8

The Balancing Act: Alyssa Cartwright 10

Three from EECS Win Lemelson-MIT Student Prizes 11

EECS Senior Wins ‘Jeopardy’ College Championship 13

StartMIT: Make It Your Business 15

StartMIT’s Innovation Night 17

StartMIT: Entrepreneurship in Action – on Two Coasts 19

The Engine: Up and Running 21

Masterworks and EECScon: Showcasing Students’ Work 23 More than 150 students presented their work during the midyear SuperUROP Research Review.

magine you’re walking in your dimly lit hallway. You’ve Idonned a pair of glasses that augment your reality. But the BOTS, BIT new object in your environment — a sleeping dragon the size of a cat — looks disappointingly flat and cartoonish.

“You can tell it’s really fake, because the lighting [on it] doesn’t FLIPS, AND match your environment,” explains Elisa Young. A senior in MIT’s Department of Electrical Engineering and Computer Science (EECS), Young is researching how to make simulated objects reflect the light in a user’s environment. That way, they CATCHING could look more like objects in the real world. “I have such love for visual things in combination with computer science,” says Young, who is enthused to erode THE BUS the boundary between virtual and concrete realities. She smiles at the thought. “It’s really cool to be like, ‘Oh, I’m living in a movie.’”

Engineering undergrads showcase Young was among 151 students presenting their work their research after one semester of during the December 2016 SuperUROP Research Review. yearlong SuperUROP projects. Students enrolled in the School of Engineering SuperUROP program — an advanced Undergraduate Research By Alison F. Takemura | EECS Opportunities Program (UROP) — who undertake yearlong research projects shared their first term’s progress with faculty and graduate student mentors.

The relevance of the students’ work — research to enable faster commutes, use robots to help people, optimize buildings, and bolster defenses against massive cyberattacks — made an impression. “The students show incredible enthusiasm for their work,” says Anantha Chandrakasan, EECS department head. “It’s amazing to see them tackling

4 features CONNECTOR 2017 eecs.mit.edu these tough problems.” Chandrakasan created the program framework. They all have embodied carbon, or the carbon in 2012 to provide students with an immersive, graduate-level emissions associated with their production. “I’m finding research experience. ways to minimize these materials to create more sustainable structures,” she says. Cooper Sloan wants to make catching the bus easier using machine learning, a technique that allows computers to pick Valerie Sarge is working on hardware, trying to do out subtle patterns. Using the last five years of GPS data from more with less data. An EECS junior, Sarge is researching Boston buses, Sloan is unraveling the dynamics of the bus how to transform low-resolution images into high-resolution system, which has some quirks. “Slow buses tend to get slower facsimiles. By using field-programmable gate arrays, and fast buses tend to get faster, which results in clumping,” or FPGAs, she can program hardware with a neural net says the EECS senior. Training a neural net, the architecture to extrapolate information, mimicking the way a human by which machines learn, will enable software to better predict would fill in the dots: “We quickly hallucinate the information bus arrival times — something commuters are waiting for. that your brain expects to see.” That means you could download a low-resolution video onto your phone, and watch Machines could also better assist people right in their homes, it in high-definition. including senior citizens who have trouble walking. To that end, Alex LaGrassa is training robots to understand human The goal is to push current limits of computing power by speech. Right now, robots can easily act on pre-programmed moving some of the computational demand from software into information, she explains — for example, “Grab the Blue hardware. If scientists can achieve that, Sarge says, “every Ribbon muffin mix.” Yet in the flurry of a real kitchen, a person type of research, every type of analysis, every type of study might say “grab the blue box,” using a description rather than that requires computing power will become easier.” a proper name. An EECS junior, LaGrassa is programming a robot to understand natural speech and actively search for Another SuperUROP is preparing hardware for space. objects that meet the human speaker’s criteria. “It has that Madeleine Waller, an EECS senior, is running tests to make extra step of figuring out ‘What is this person talking about?’” the Transiting Exoplanet Survey Satellite (TESS), scheduled for she says. Having robots bridge that linguistic divide between launch in December 2017, more resilient. human and machine would be helpful “because, you know, requiring people to know how to program is problematic,” The satellite will contend with meddlesome cosmic rays, which LaGrassa says. can cause computer chip bits to flip, creating errors in the data. Waller is testing the satellite’s FPGA by intentionally injecting Brenda Stern, a senior in civil and environmental engineering, errors into a model data stream. “We’re trying to trigger all the is looking to design buildings with a smaller carbon footprint. watchdog protocols in the system,” she says. Ensuring they Most people of think of the energy consumed during work would give researchers a better chance of confidently construction or once a building is up and running. But Stern detecting exoplanets. focuses on the energy that went into creating the building materials, such as the concrete or steel columns, slabs, and But while some threats to systems are random, others are maliciously calculated. In October, Hyunjoon Song, a senior in EECS, saw news that millions of infected bots had attacked Akamai, a network server company. The strike had wielded an army of “Internet of Things” devices, such as digital cameras and video recorders. Collectively dubbed the Mirai botnet, the bots battered Akamai with 620 Gb per second to attempt to overload the company’s servers in what’s known as a distributed denial of service (DDoS) attack. “This was one of the most powerful DDoS attacks ever,” he says. “And the problem is that there are billions more of these devices that are just as vulnerable. The Mirai botnet is just the beginning.”

Song is looking at the source code and interacting with the Mirai botnet to understand its architecture and sift for vulnerabilities, in the hope of preventing more serious attacks.

SuperUROP continued through the spring semester, with many students presenting the results of their research at EECScon, MIT’s annual undergraduate research conference, in April and an awards and certificate program in mid-May.

For more about SuperUROP, visit superurop.mit.edu and The event gives SuperUROP participants a chance to discuss their research projects with faculty, graduate students, and other attendees. eecs.mit.edu

eecs.mit.edu 2017 CONNECTOR features 5 WHEN USAGE SPEAKS, EECS LISTENS

Student group provides first-hand feedback on Course 6 issues ranging from class sizes to curriculum changes.

By Kathryn O’Neill | Connector Contributor

hen big changes are afoot in Course 6 — and even Wwhen the changes are small — students involved in the Undergraduate Student Advisory Group in EECS (USAGE) have their fingers on the pulse of the department.

Founded during the 2011–2012 academic year, USAGE is an advisory committee of about 30 students who provide the leaders of MIT’s Electrical Engineering and Computer Science Department (EECS, also known as Course 6) with insight into the how the department’s nearly 1,500 undergraduates view curriculum changes, workload, and more.

“I see us as kind of a sounding board for the department,” says Natalie Lao, a graduate student in the Master of Engineering (MEng) program, who has served on the committee since her freshman year. “Empowerment is a big part of USAGE. If you want to see something change in Course 6 and it’s reasonable — and other people agree with you — it’s one of the best ways Front row, left to right: Lisette Tellez, Sravya Vishnubhatla, Sarah Hensley, Allison Lemus | Back row, left to right: Matthew Kalinowski, Jimmy to have your voice heard.” Mawdsley, Ignacio Estay Forno, Natalie Lao, Anish Athalye

Over the years, USAGE has helped shape such signature EECS offerings as SuperUROP, the fast-growing advanced Undergraduate Research Opportunities Program (UROP), and StartMIT, an intensive workshop on entrepreneurism offered Lao found the experience of preparing a report for the 2015 during MIT’s between-semesters Independent Activities Period Visiting Committee quite valuable. “That was a big project, and (IAP). In 2014, feedback from USAGE prompted the creation of I learned a lot from doing it,” she says, noting she particularly a new undergraduate student lounge in Building 36; this year, enjoyed relating USAGE’s findings to the impressive roster members have helped guide the renovation of another lounge of academics and professionals who serve on the Visiting in Building 38. Committee. “That was really awesome because we got to present our thoughts to all these world leaders in tech.” “It’s great to get student input on issues of importance to them before we implement a program,” says Anantha P. Members of USAGE also met with this year’s Visiting Chandrakasan, the Vannevar Bush Professor of Electrical Committee, providing input that is “extremely valuable,” Engineering and Computer Science and EECS department Chandrakasan says. “This helps us address issues of head. “They give us a different perspective and bring up things importance to students, such as class size, workload, and ways to think about.” we can make the department more inclusive.”

Among its many contributions, USAGE regularly represents USAGE meets every few weeks during the school year, which the student perspective on Course 6 to the Visiting Committee can be a significant time commitment for any student, but that evaluates the department every two years on behalf of members say they participate to give back to the department. the MIT Corporation (the Institute’s governing board). USAGE “It’s a way for me to contribute and make Course 6 a better surveys students about such issues as workload, curriculum, place,” Lao says. “I’m part of this community, and it’s great to and advising, and then produces a brief report; members see it growing and becoming better.” later meet with the Visiting Committee to present the group’s findings. In addition, USAGE provides students with “an exceptional opportunity to see how the department functions at a high

6 features CONNECTOR 2017 eecs.mit.edu “ Empowerment is a big part of USAGE. If you want to see something change in Course 6—and other people agree with you—it’s one of the best ways to have your voice heard.” Photos: Anne Stuart —Natalie Lao, long-time USAGE member Front row, left to right: Uttara Chakraborty, Alyssa Cartwright, Nalini Singh, Nancy Hung Back row, left to right: Allan Sadun, Daniel Richman, Billy Caruso, Kai Aichholz, Alexander Sludds, Isaac Kontomah | Not pictured: Efe Akengin, Suma Anand, Logan Engstrom, Hassan Kane, Keertan Kini, Aneliese Newman, Alisha Saxena, Alex Sloboda, Tejas Sundaresan, Sarah Wooders level,” says Kai Aichholz, a group member and senior in For example, HKN was able to approach USAGE this fall to electrical engineering and computer science. advocate for the Chu Lounge renovation. With USAGE’s support, the project quickly gained ground; students discussed how the For example, just over the course of this year, USAGE has space could be repurposed and then worked together to help discussed such department concerns as faculty advising and redesign the lounge to include new furniture, new electronics, teaching loads, training for teaching assistants, and the and card-reader access. system for flagging students based on academic performance. The group also heard several presentations. Chancellor Cynthia “We really pushed for it to be a dedicated social space, and Barnhart described how MIT is working to become more the department accepted that,” says Alisha Saxena, a junior attractive to admitted students. Clinical Director for Campus in electrical engineering and computer science and a USAGE Life Maryanne Kirkbride discussed the Institute’s efforts to member who is also president of the MIT IEEE/ACM Club. “It’s improve students’ overall well-being. Asuman Ozdaglar, a going to be great for my club. We can hold more social events.” professor of electrical engineering and computer science and EECS associate department head, outlined a proposed new Ultimately, USAGE’s impact is “a lot of small things that add interdisciplinary major. up,” says Anish Athalye, who is completing both his senior year in computer science and engineering and his MEng degree. Nalini Singh, a senior in electrical engineering and computer “The department does take our feedback into account, which I science, says she values her USAGE participation because think is great.” it gives students a direct line of communication to EECS leaders. “This is an efficient way to raise concerns with the department,” says Singh, who is also president of MIT’s chapter of the national honor society Eta Kappa Nu (HKN).

eecs.mit.edu 2017 CONNECTOR features 7 Photo: Rachel van Heteren

eertan Kini can sum up his approach to life at MIT in one Ksentence. “When you’re part of a community, you want to HELPING leave it better than you found it,” says Kini, a graduate student in the Department of Electrical Engineering and Computer Science (EECS, also known as Course 6). That philosophy has guided Kini throughout his years at MIT, as he works to POLICY AND improve policy both within the Institute and beyond. As a member of the Undergraduate Student Advisory Group (USAGE), former chair of the Course 6 Underground Guide TECHNOLOGY Committee, and a member of the Internet Policy Research Initiative (IPRI) and the Advanced Network Architecture Group, Kini has focused his research on finding ways that technology and policy can work together. As he puts it: “There can be WORK unintended consequences when you don’t have technology makers who are talking to policymakers and you don’t have policymakers talking to technologists.” His goal is to allow them to talk to each other.

TOGETHER At 14, Kini first started to get interested in politics. He volunteered for President Obama’s 2008 campaign, making EECS graduate student Keertan Kini is calls and putting up posters. After that, he was campaigning for working to strengthen the intersection between a ballot initiative to raise more funding for his high school. He hasn’t stopped being interested in public policy since. the two fields.

By Rachel van Heteren | EECS High school was also where Kini became interested in computer science. He took a computer science class in high school at his sister’s recommendation, and in his senior year, he started watching computer science lectures on MIT OpenCourseWare (OCW) by Hal Abelson, the Class of 1922 Professor of EECS.

8 features CONNECTOR 2017 eecs.mit.edu “That lecture reframed what computer science was. I loved it,” Kini recalls. “The professor said, ‘It’s not about computers, and “There can be it’s not about science.’ It might be an art or engineering, but it’s not science, because what we’re working with are idealized components, and ultimately the power of what we can actually unintended achieve with them is not based so much on physical limitations so much as the limitations of the mind.” consequences when In part thanks to Abelson’s OCW lectures, Kini came to MIT to study electrical engineering and computer science. He received an SB in EECS in 2016 and is now completing a master of you don’t have engineering (MEng) degree.

Combining two disciplines technology makers Kini set his policy interest to the side his freshman year, until who are talking to he took the Foundations of Information Policy class (6.805J) with Abelson, the same professor whose lectures had attracted him to computer science in the first place. After that, Kini policymakers and joined Abelson and Daniel Weitzner, a principal research scientist in the Computer Science and Artificial Intelligence Laboratory (CSAIL), in putting together a big data and privacy you don’t have workshop for the White House in the wake of the Edward Snowden leak of classified information from the National Security Agency. Later, Kini became a teaching assistant policymakers talking for 6.805J.

With Weitzner as his advisor, Kini went on to work on a to technologists.” SuperUROP, an advanced version of the Undergraduate —Keertan Kini Research Opportunities Program (UROP) in which students undertake an intensive research project for a full year. Kini’s project focused on making it easier for organizations that had experienced a cybersecurity breach to share how the breach undergraduate lounge, and compiling a list of the resources happened with other organizations, without accidentally available to EECS students. He is especially interested in releasing private or confidential information as well. making sure students know about the MIT resources for prospective entrepreneurs. Among them: StartMIT, an Typically, when a security breach happens, there is a “human intensive Independent Activities Period (IAP) workshop bottleneck,” Kini says. Humans have to manually check designed to help students learn what’s involved in launching all information they exchange with other organizations to a startup. ensure they don’t share private information or get themselves into legal hot water. The process is time-consuming for all “At MIT, we try to solve very difficult challenges, we try to solve organizations involved. Kini created a prototype of a system that very meaningful technical problems,” Kini says. “But what gets could automatically screen information about cybersecurity lost in the shuffle is: After you come up with a great idea, how breaches, determining what data had to be checked by a do you get it out of your head and into the world?” StartMIT human, and what was safe to send along. helps bridge that gap, he says.

Once finished with his SuperUROP, Kini became involved in the Thanks to his own StartMIT experience, Kini knows that he development of Votemate, a web app designed to simplify voter wants to launch a business one day. “I see starting a company registration nationwide. But Kini’s interest in Votemate wasn’t not only as an option, but the option,” he says. “It’s a way to only about increasing the number of people who register. “I make sustainable change in the world.” think most people in this nation are centrist, and one of the reasons our political system gets polarized is because people Editor’s Note: In May 2017, EECS recognized Keertan Kini’s who are polarized primarily turn out to vote,” he says. He contributions with a Paul L. Penfield Student Service Award. believes the only reliable solution is increasing the number of people who actually cast ballots.

Shaping policy on campus

Kini is also involved in making changes within the Institute. As a member of the Undergraduate Student Advisory Group (USAGE), Kini has been involved in exploring ways to revitalize the electrical engineering curriculum, redesigning the eecs.mit.edu 2017 CONNECTOR features 9 THE BALANCING ACT

Alyssa Cartwright engineered a rich MIT experience that included coursework, research, music — and more.

By Anne Stuart | EECS

lyssa Cartwright’s first order of business at MIT didn’t Ainvolve science or technology. “One of the biggest things I had to do when I got here was learn to prioritize,” says Cartwright, a member of the class of 2017. “I had to learn to do my work in an efficient manner to have time left for what was important to me.”

Apparently, she aced that lesson, managing to balance her studies in electrical science and engineering (6-1) with other activities that included co-chairing MIT’s largest student-run Serving on the EECS student advisory committee was just one of research conference and serving on an elite group that meets Alyssa Cartwright’s activities at MIT. regularly with the leadership of the Department of Electrical Engineering and Computer Science (EECS). Along the way, she spent a summer conducting research in a National Science Foundation-funded program at Vanderbilt University experience with optics and biology, and that’s where I learned in Nashville, Tenn., collected two EECS awards for her that I wanted to focus in that area,” she says. She also loved Undergraduate Research Opportunities Program (UROP) and collaborating with her peers at Vanderbilt: “You live with the SuperUROP projects, served as a teaching assistant — and still other students who are doing the program; you go to the labs found time to play clarinet in the MIT Symphony Orchestra all and do your work and talk about it later,” she recalls. “It’s like four years. a mini-graduate school.”

Cartwright, who is from Williamsville, N.Y., just outside Buffalo, In the fall of 2017, Cartwright will start graduate school jokes that she grew up with both sides of Course 6: her father for real, working toward a PhD in electrical engineering at is an electrical engineer; her mother is a system administrator. Stanford University. She plans on an academic career, but isn’t “From an early age, I thought engineering was a very cool sure yet where that will take her. field,” she recalls. Meanwhile, she offers this recommendation to future EECS Music has also long been part of her life. She began playing students: “Get involved with research as soon as you can — the clarinet in the fourth grade, which led not only to a spot in even if you feel you are wildly underqualified,” she says. “The MIT’s orchestra, but to a minor in music as well. “Music is a faculty are invested in their students. If you put your time into very important part of my personality and my worldview and the experiences, they’ll put in the time to help you.” And, as a how I approach things,” she says. “It’s really important to me to member of two engineering honor societies, she acknowledges have a creative outlet.” that academics are crucial — but only part of the overall MIT picture. “Try not to stress too much about classes,” she Cartwright found her research focus in 2015, when she was advises. “There are other parts of life here.” among 17 students from throughout the United States who participated in Research Experience for Undergraduates (REU) Editor’s Note: In May 2017, EECS recognized Alyssa Cartwright’s at Vanderbilt. Her project involved designing, simulating, and contributions with a Paul L. Penfield Student Service Award. testing photonic crystals for biosensing. “That was my first

10 features CONNECTOR 2017 eecs.mit.edu THREE FROM EECS WIN LEMELSON-MIT STUDENT PRIZES EECS seniors Chandani Doshi and Tania Yu were part of Team Tactile, which invented a portable, real-time text to braille converter. PhD candidate Apoorva Murarka developed technology designed to more efficiently produce high-fidelity sound.

By Anne Stuart | EECS Photo: Brian Smale, Microsoft

Left to right: Chandra Doshi, Jessica (Jialin) Shi, Chen (Bonnie) Wang, Charlene Xia, Tania Yu, and Grace Li of MIT’s winning undergraduate Team Tactile

hree students in the Department of Electrical Engineering Murarka developed a 125-nanometer-thick membrane — Tand Computer Science were among the winners of the 2017 approximately one-thousandth the width of a human hair — to Lemelson-MIT Student Prizes, which are designed to honor the produce high-fidelity sound more efficiently. This technology nation’s most inventive college students. can be applied to hearing aids, earphones, or other consumer electronic devices, resulting in superior sound quality and The prizes, presented in April by the Lemelson-MIT Program, longer battery life. Murarka previously received bachelor’s and honored the EECS students for their inventions in the “Use master’s degrees in electrical engineering from MIT. it!” category, which focuses on technology that can improve consumer devices. Celebrating young inventors

Chandani Doshi and Tania Yu, both seniors in EECS, were part The Lemelson-MIT Student Prize is a national collegiate of MIT’s Team Tactile, the $10,000 Lemelson-MIT “Use it!” invention prize program, supported by the Lemelson Undergraduate Team Winner. The six-member team developed Foundation, which celebrates young inventors who have Tactile, a portable device that converts text to braille in real designed and built prototypes of inventions to solve social time. The technology allows people who are visually impaired problems. For 2017, the Lemelson-MIT Program honored four to take a picture of printed text, which is then transcribed to undergraduate teams and five individual graduate inventors. braille on a refreshable display. Other Team Tactile members “These students display the brilliance and hope of their include Grace Li, Jessica (Jialin) Shi, and Charlene Xia, all generation,” said Dorothy Lemelson, Lemelson Foundation seniors in the Department of Mechanical Engineering (MechE), chair. “We are proud to recognize them for their achievements.” and Chen (Bonnie) Wang, a senior in the Department of Materials Science and Engineering. Students entered their technology-based inventions in “Use it!” and three other categories: “Cure it!” (for improving Apoorva Murarka, a PhD candidate in electrical engineering, health care), “Drive it!” (for improving transportation), and was the $15,000 Lemelson-MIT “Use it!” Graduate Winner. “Eat it!” (for improving food or agriculture). Other 2017

eecs.mit.edu 2017 CONNECTOR features 11 StartMIT, covered elsewhere in this section, offers another opportunity for young entrepreneurs and inventors to hone their ideas and hear from the pros. Following are some tweets from the 2017 StartMIT experience.

@ahamino: Awesome startup vibe @medialab StartMIT innovation night. Graduate winner Apoorva Murarka, PhD candidate in electrical engineering

@MIT_Alumni: @drewhouston ’05 stops by Lemelson-MIT Student Prize winners from MIT included @MITEECS’s #StartMIT to talk collaboration, two PhD candidates in mechanical engineering and one in managing scale and @Dropbox. aeronautics and astronautics. The Lemelson-MIT Program also honored graduate students or undergraduate teams from Stanford University, the University of California Berkeley, the University of Iowa, and the University @jpenswick: Proud to represent of Maryland. @cmtelematics at the #StartMIT Innovation Event tonight. Lemelson-MIT Student Prize applicants were evaluated by screening committees with expertise in the invention categories as well as by a national judging panel of industry leaders. Screeners and judges assessed entries on the @kochinstitute: Drop and give me breadth and depth of inventiveness and creativity, potential career advice: Bob Langer & Susan for societal benefit and economic commercial success, Hockfield impart wisdom at StartMIT’s impact on community and environmental systems, and the candidates’ experience as role models for youth. entrepreneurship boot camp.

To learn more about the Lemelson-MIT Program, including instructions on applying for future prizes, @TriciaCotter:#StartMIT @eship visit lemelson.mit.edu @aulet Great teams presenting from the MIT ecosystem.

“These students @juanleungli: Amazing @MIT support for Boston founders. Inspiring speakers… display the brilliance Fired up for future #startmit

@iza_wit: Feel[s] strange in some ways and and hope of their so wonderful, having 6 women on a panel at a tech conference and it’s not a [women’s generation.” conference] #StartMIT @MITEECS @MIT —Dorothy Lemelson, Chair, The Lemelson Foundation @jeanhammond: @ktrae Katie Rae telling how entrepreneurship thinking can drive change as a part of a panel of innovative women #StartMIT

12 features CONNECTOR 2017 eecs.mit.edu EECS SENIOR WINS ‘JEOPARDY’ COLLEGE CHAMPIONSHIP

Lilly Chin takes the $100,000 grand prize, surpassing 14 on-air contestants and thousands of applicants from colleges around the United States.

By Elizabeth Durant | Office of the Dean for Undergraduate Education Photo: Jeopardy Productions Inc.

EECS senior Lilly Chin, the newly crowned “Jeopardy!” College Champion, with program host Alex Trebek

et’s be honest: Even the most disciplined college students The making of a “Jeopardy!” champion Ldon’t pay attention all the time during their classes. The temptations of a hushed conversation with a classmate, a Chin was one of thousands of students from schools around daydream, or any number of digital distractions can be hard the United States who applied to be contestants on the show. to resist. Of those, 250 were invited to in-person auditions in New York City in November, which consisted of a written test, gameplay, But one could argue that senior Lilly Chin had an excellent and an interview. In December, Chin learned she’d made the excuse for tuning out during one of her comparative media cut — a total of 15 students and one alternate — and the show studies classes in October 2016: She was taking a 10-minute was taped in Jan. 10-11 in Los Angeles. Sworn to secrecy for online test to qualify for the popular TV quiz show “Jeopardy!” several weeks after that, Chin was able to savor the victory in It was only offered on one specific date, at one specific time — late February at a final episode screening held in Room 4-237, which happened to be during class — so she had little choice. where she was cheered on by dozens of friends and other fans “I was trying not to get caught by the teacher while I was from the MIT community. answering the questions,” she later confided to a “Jeopardy!” film crew, barely suppressing a giggle. Chin, an electrical engineering and computer science major with a minor in mechanical engineering, credits part of her In the end, it was worth the risk. Chin went on to become a success to her curiosity about media, which led her to also contestant on the show, made it to the finals, and walked away minor in comparative media studies. She loves “investigating with the college championship title and the tidy sum different forms of media, whether it’s film, video games, or of $100,000. children’s literature — [it’s] the same curiosity which leads me to seek out factoids about these media, and which tend to get asked about more on ‘Jeopardy!’” eecs.mit.edu 2017 CONNECTOR features 13 A native of Decatur, Georgia, Chin is no stranger to trivia competitions; she participated in quiz bowls from fifth grade “The best part of being through high school. She prepared for “Jeopardy!” in a myriad of ways, such as reviewing her old trivia books, reading web comics, listening to Top 40 music, and generally spending lots on the show has of time “goofing off on the Internet.” She found creative ways to bolster her knowledge of subjects she didn’t know well; to address a weakness in history, she crammed The Cartoon definitely been the great History of the Modern World. outpouring of support Chin enlisted the help of MIT friends to study and practice her gameplay, including playing Protobowl, a real-time, multi- player quiz bowl application created by her classmate, senior the MIT community has Kevin Kwok. She also sought advice from two MIT connections who had “Jeopardy!” experience: her former graduate resident given me.” tutor, Philip Arevalo (who motivated her to apply for the show), and Pranjal Vachaspati ’14. —Lilly Chin, EECS senior and “Jeopardy!” champion Preparation aside, Chin also had a few tricks up her sleeve. One of them was buzzer strategy. “I think the game is actually more about buzzer strategy than trivia,” she says. Timing is everything: buzz too soon, before show host Alex Trebek finishes reading the clue, and your buzzer will get locked out for a fraction of a second — enough time for an opponent President L. Rafael Reif, Chancellor Cynthia Barnhart, and Vice to buzz in. The key is to time it precisely when Trebek is President and Dean for Student Life Suzy Nelson were among done speaking. those rooting for her. “If the clue is ‘Nerd Pride,’ the answer must be, ‘What was our overwhelming reaction when we Her board strategy paid off, too. In the more conventional learned that Lilly Chin just won College Jeopardy?’” Reif wrote approach, contestants work their way through one category, in an email to Chin. “Even better, for this longtime professor: moving from lower-value clues at the top of the board to You’re not just MIT, you’re EECS! Lilly, I hope you have a higher-value clues at the bottom. Others, like Chin, prefer to moment to savor this terrific achievement.” jump between categories and choose clues further down the board. “It’s a bit of a controversial strategy,” she says. But the “[Provost] Marty Schmidt and I have decided you are the Tom advantage is that skipping around the board can throw off your Brady of ‘Jeopardy’ — great job!” Barnhart said in an email to opponents and increase your odds of finding the clue with the Chin, following Chin’s second-to-last appearance on the show. Daily Double. “The Daily Doubles aren’t evenly distributed,” Nelson wrote Chin after her strong showing in the first week: Chin explains. “People have run stats and found they tend to be “I’m so proud of your Jeopardy performance…Plus, love your in the fourth row or so.” strategy of finding those Daily Doubles — bold and fearless.” Being on the show was “surreal,” Chin recalls, smiling broadly. Chin developed a large fan base among MIT students, who “There was a moment when all the contestants realized that found creative ways to show their support, throwing screening this was actually happening. After the game, everyone’s hands parties and sharing their favorite moments on social media. were shaking.” To combat her own nerves, she channeled her One friend, Shi-Ke Xue ’16, created a series of GIFs of Chin on experience on the trap shooting team (part of the MIT Sporting the show and shared them on Reddit. Clays Association), in which players shoot moving clay targets with a shotgun. “The coach is always like, ‘Don’t keep track of the score, just take it one shot at a time,’’ she says, “because Looking back, and ahead especially for shooting, any sport, you need to be calm. As soon as you start thinking, ‘Oh no, what-ifs,’ then your game gets off In retrospect, Chin admits she feels a bit bad about taking the and you miss everything. So I think that really helped.” “Jeopardy!” online test during class back in October, adding, “That is one of my favorite classes.” Luckily, her professor — “Nerd pride” T.L. Taylor, professor of comparative media studies, who also followed Chin’s progress on “Jeopardy!” and is now privy to Chin’s secret about the test — loves the anecdote. “How very Throughout the course of the two-week tournament, as word apropos,” she says, “considering it was a class on games spread about her progress, Chin developed quite a following and culture!” on the MIT campus. “The best part of being on the show has definitely been the great outpouring of support the MIT community has given me,” she says. “At first, I was a bit Chin, who plans to begin a PhD program in robotics after embarrassed about being on national television and tried to graduation, says she’ll use the prize money to pay off college keep the whole thing under wraps. But soon, I found that the loan debt and to travel to a few research conferences around more people that I told, the more I found that people were the world on video game studies — a form of media that eager to help and support me.” continues to pique her boundless curiosity.

14 features CONNECTOR 2017 eecs.mit.edu MAKE IT YOUR BUSINESS

StartMIT, a boot camp on entrepreneurship, gives students an intimate look into what it takes to build a company. Photo: Rose Lincoln By Alison F. Takemura | EECS

As part of StartMIT, Dropbox CEO Drew Houston ’05 (seated, front left) visited campus to meet student innovators and discuss his latest projects.

f you daydream about founding a startup, know this: CEOs Scientists and engineers often find themselves wanting to turn Iare made, not born. Theodora Koullias ’13 — founder of the their research into a product, said Institute Professor Robert tech-fashion company Jon Luu — summed it up this way: Langer, an invited speaker. “We want to see it get out to the “You learn on the job all the time.” world and help people.”

Koullias candidly shared her experience with students and But founders need grit, said Langer, who holds more than postdocs during StartMIT 2017. The short course, which is 1,000 pending and issued patents. In his view, the defining packed with practical instruction and mentorship, is designed characteristic of students who have become successful to give aspiring entrepreneurs a boost up the founder learning business leaders is their willingness “to walk through walls curve. Held during MIT’s Independent Activities Period (IAP) in to get their technology out into the world.” January, StartMIT gave participants a chance to form teams and develop their ideas into venture capital-worthy pitches. Ray Stata ’57, cofounder of Analog Devices, Inc. and Students learn about the smorgasbord of ingredients that go leader in the design and manufacture of analog and digital into making a startup: creating a value proposition, staking signal processing semiconductors, didn’t sugar-coat the a claim to intellectual property, working with the press, entrepreneur’s brand of determination. “When you start a networking, creating culture, and, of course, raising money. company, there is no work-life balance,” he told students. “You continue to drink from the fire hose not only because “StartMIT featured some amazing speakers who engaged you have to, but because you are so committed and motivated actively with our students on all aspects of starting a company, to succeed.” giving them a glimpse of what an entrepreneurship career is,” said StartMIT lead organizer Anantha Chandrakasan, Wen Jie Ong, a PhD candidate in chemistry, is determined the Vannevar Bush Professor of Electrical Engineering and to get his innovation to the public because he sees his Computer Science (EECS) and EECS department head. The technology’s relevance. He’s been developing a polymer that course was developed by EECS and supported by the MIT removes lead from contaminated water, making it safe to Innovation Initiative. drink. To underscore the need, Ong pointed not only to the recent water crisis in Flint, Mich. — in which the city’s 100,000 eecs.mit.edu 2017 CONNECTOR features 15 residents have had to grapple with lead, a neurotoxin, in their “I want to stay in academia more than become an drinking water — but also to examples that are closer to entrepreneur,” Yazicigil said. “But I see how they’re able to home. For example, as of November 2016, drinking water at still do both at the same time.” 164 public schools in Massachusetts had lead levels above regulatory limits. Dozens of other pioneers also shared their experiences during the course, including emphasizing the importance of StartMIT, Ong said, “is a large time commitment, but it’s totally communicating, building trust with funders, and assembling worth it.” The course exposed him to new ideas through its star an excellent team. speakers, and put him in touch with mentors, including venture capitalists, who gave him “very frank” advice, he added. He In addition, StartMIT allowed students to explore the couldn’t have gotten that anywhere else. entrepreneurial ecosystem beyond MIT. Students took field trips to Ministry of Supply, an innovative fashion company Direct feedback is priceless, said Susan Hockfield, who served founded by MIT alumni; venture capital firms Pillar VC, as president of MIT from 2004 to 2012. She told the class that, Bolt, and Project 11 Ventures; the non-profit startup at her very first poster presentation as a graduate student, accelerator MassChallenge; and the Cambridge Innovation she hadn’t realized people would actually want to talk with Center, which houses several MIT startups. The Institute also her about her work. So, unprepared, she rambled. Afterward, has a wealth of opportunities to support student ventures. she spoke to her advisor standing nearby, telling him: “I really Several teams will be using MIT’s Venture Mentoring Service. felt stupid over there.” His response? “Yeah, you sounded Some have applied to MIT’s Sandbox Innovation Fund, an pretty stupid.” Institute-wide program providing support, mentor matching, and funding to help qualified students and teams nurture their Hockfield appreciated that unfettered honesty. She encouraged creative brainstorms. the audience to “find someone who’s willing to tell you as it really is.” Interpersonal connections represent a big part of what makes StartMIT so useful, said Anna Fountain, a senior in mechanical Lyric Jain hopes to make the media that people consume engineering. “It makes me feel a lot more comfortable knowing every day into a similarly unbiased resource. “Polarization in that there are people who can help us and who have done this the media is a big problem,” the Cambridge University-MIT before, right here in the greater MIT community.” exchange student in mechanical engineering said during one of the course’s networking lunches. For more about StartMIT, visit startmit.mit.edu

To broaden readers’ perspectives, Jain is working on a web platform that delivers news from across the liberal- conservative political spectrum of media outlets, from MSNBC to Fox News. In addition, his technology is designed to automatically prune the stories to their facts, lining them up for readers as different sides of a debate.

During StartMIT, Jain’s project was still in its early stages, and he started the course with his guard up. “Initially, I was quite suspicious that if I talk to someone, they’re going to steal my idea,” he said. “But now I know the idea is only one small part of it. What matters is how you build on the idea, put your twist on it, and build a team around it.”

Besides, there are pluses to being open, he added: “Talking to people about your idea, you’re going to get input to make it better. They might even be a potential customer.”

Rabia Yazicigil, a postdoctoral associate in EECS, has noted the risk posed by devices that communicate with each other — components of the so-called Internet of things (IoT). A hacked pacemaker, for example, could be a potential murder weapon. To prevent that gruesome possibility, Yazicigil is developing a new kind of secure wireless communications system for StartMIT lead organizer and EECS department head Anantha Chandrakasan IoT devices. and former MIT President Susan Hockfield discuss leadership.

Before StartMIT, Yazicigil had some reservations about starting a company. Hearing from scientists who became business leaders — including Hockfield, Langer, Stata, and Michael Stonebraker, adjunct professor of computer science at MIT and co-director of the Intel Science and Technology Center — helped Yazicigil see a path for herself.

16 features CONNECTOR 2017 eecs.mit.edu STARTMIT’S INNOVATION NIGHT Women entrepreneurs from a range of fields discuss their pioneering work and what they learned along the way.

By Terri Park | MIT Innovation Initiative Photos: Rose Lincoln

As part of StartMIT, six distinguished women discussed their experiences with innovation — and shared their advice with next-generation entrepreneurs.

nnovators in materials chemistry, online care, natural I thought ‘this is the only thing that I want to do,’” she recalled. Ilanguage processing, social robotics, and venture capital Since then, she’s applied her accomplishments to other fields shared their founders’ journeys in a lively panel discussion she’s never explored before, such as cancer. “You’re going to during StartMIT. run into obstacles along the way, but you learn these aren’t failures; these are learning experiences,” she said. “Not Led by moderator Kym McNicholas, an Emmy Award-winning everyone’s going to agree with you. If more people don’t anchor/reporter/producer and entrepreneur, the cast included agree, it’s probably a better idea. You keep going.” MIT faculty members Regina Barzilay, the Delta Electronics Professor of Electrical Engineering and Computer Science Like Belcher, Barzilay followed her passion by taking her (EECS); Angela Belcher, the James Mason Crafts Professor core research focus of natural learning processing in a new in the Department of Materials Science and Engineering direction after undergoing treatment for breast cancer, when and the Department of Biological Engineering; and Cynthia as a patient, she was surprised to learn that data science and Breazeal, associate professor of media arts and sciences. machine learning weren’t used in cancer care in the United Also participating were Donna Levin, co-founder of Care. States. “The technology used on Amazon to recommend com, entrepreneur-in-residence at the Martin Trust Center products was much more sophisticated than what we have for Entrepreneurship, and lecturer at MIT Sloan School of today in cancer care,” she said. Barzilay set about on a new Management; and Katie Rae, then founder and general partner journey: in collaboration with researchers at Massachusetts at Project 11 Ventures (later named president and CEO of The General Hospital, Barzilay and her team built a system that Engine, MIT’s new startup accelerator). takes breast pathology and automates the data analysis in a new way with a high level of accuracy. The team is using deep Common themes of passion and timing emerged throughout learning to analyze mammogram readings with the goal of the conversation as McNicholas asked the panel about topics using this data to make predictions which humans currently related to risk, research, inspiration, and failure. cannot do.

For Belcher, risk wasn’t a factor when she decided to direct her Shifting the focus to timing, McNicholas turned to Breazeal, a career into the idea of genetically programming organisms to pioneer in social robotics and the founder and chief scientist grow into electronics and batteries — a proposal that was met of Jibo, which recently introduced the world’s first social robot with much skepticism when she was a young professor getting for the home. When asked about the moment the research her start. “I didn’t think of it as risky at the time. went from the lab to commercialized product, Breazeal said: eecs.mit.edu 2017 CONNECTOR features 17 “I didn’t know when I was starting this work that I would be an exposed students to the basics of entrepreneurship. During the entrepreneur. But over time, watching technology, watching the two-week program, undergraduates, graduate students, and cloud-computing revolution, watching the mobile-computing postdocs heard about entrepreneurship from a variety revolution, [I started] thinking the elements are coming of viewpoints. together. All of these really hard subfields were starting to get to the level that you could start building on to create this new Before the discussion, guests mingled with alumni kind of medium. When you think about a social robot, it’s a new entrepreneurs and innovators during a Startup Showcase kind of medium for social communication and interaction.” and learned about early-stage ventures from MIT. In addition, Bottom line: “Now was the time to jump in,” she said. “Timing EECS department head Anantha Chandrakasan, the Vannevar is everything.” Bush Professor of Electrical Engineering and Computer Science, welcomed the audience and introduced The Engine, McNicholas asked Levin, the cofounder of Care.com, how to which focuses on providing support for the biggest and most know when the time is right. “You don’t want to be too early,” transformative technology-based ideas that require more time Levin replied. “For us, the technology existed to find people to commercialize. online and make matches, but it was a highly fragmented market and therefore an opportunity.” Care.com is now the Joi Ito, director of the MIT Media Lab, described the innovative world’s leading online site for helping people find and manage “antidisciplinary” research happening at the lab. A longtime family care, but when Levin and her partners started pitching entrepreneur and venture capitalist, Ito spoke of the lab’s the idea, many people questioned its viability. “Who would four-pronged approach to learning: projects, peers, passion, ever go online to find care for their loved one?” Levin asked play. “This is a lot of the spirit of MIT, and it’s the spirit of rhetorically. “We decided to do something about that. Every entrepreneurship,” he said. “The best startups have all four member of the team believes he or she is going to change the of these, and a lot of what we’re doing at the Media Lab is world. It’s hard for others to compete with you if you believe instilling the values that we need in entrepreneurship so that you’re going to change the world.” we will hopefully spin out many entrepreneurs.”

Sharing the perspective from the venture capital side, Rae Developed by the Department of Electrical Engineering and spoke about taking the leap again and again. One early leap Computer Science, StartMIT is supported by the MIT Innovation involved the decision to leave her job at Microsoft to start her Initiative and chaired by Chandrakasan. own company and pursue investing in early-stage technology and software companies, where she worked side-by-side with founders to increase their rate of success. “I always thought of myself as in service to the idea of the entrepreneurial team, and that has led me all along the way,” she said. “Being an early-stage investor, my role is often to say to the founders, ‘You’re onto something amazing. Do you see the progress you made? Have you met this awesome person?’ My role is to keep that inspiration alive. I’m there to suggest, to present opportunities and collisions.”

On the topic of failure, Levin said: “It’s not ‘if’ you fail; of course you are going to fail. It always feels like failure until it’s a success. The important thing is to keep going.” To which Breazeal added: “I think resiliency to failure is important. I don’t view failures as failures. I really do view them as something that helps make me smarter. You also have to learn to distinguish thoughtful critique, which is so valuable, from just ‘squashing.’ You have to trust your gut. It’s okay not to know how. You’ll figure it out.”

McNicholas asked the panelists about the greatest lessons they’ve learned. “The process I am privileged to observe is taking things that are impossible to do and translating them into the real product that impacts people’s lives,” Barzilay replied. “It’s important to find problems which impact the bigger world, and at MIT, we’re really privileged to have this capacity.”

In closing, McNicholas advised the audience of aspiring Front row, left to right: Angela Belcher, Kym McNicholas, Katie Rae entrepreneurs to “never let what you don’t know or have never Back row, left to right: Joi Ito, Regina Barzilay, Anantha Chandrakasan, done before get in the way of achieving your dreams.” Cynthia Breazeal, Donna Levin

Innovation Night was the capstone event of StartMIT, an intensive Independent Activities Period (IAP) workshop that

18 features CONNECTOR 2017 eecs.mit.edu Photo: Mary Ellen Sinkus

Nicola Corzine, executive director of the Nasdaq Entrepreneurial Center in San Francisco, spoke with StartMIT participants during their intensive two-day trip. ENTREPRENEURSHIP IN ACTION — ON TWO COASTS StartMIT participants see innovation up close during whirlwind tour of Bay Area business ecosystem.

By Anne Stuart | EECS

or some students and postdocs, the StartMIT experience Several students said the expenses-paid trip provided an Fextended well beyond Cambridge and Boston — about 3,000 important complement to the StartMIT workshop held during miles beyond. MIT’s Independent Activities Period (IAP) in January. “The IAP class gave me a chance to start looking at possible startup In late March, 25 StartMIT participants traveled to California paths. The trip was a good incentive to continue,” said Oscar for an intensive two-day entrepreneurship program in San Moll, a PhD student in EECS. “Understanding the Bay Area Francisco and Silicon Valley. They visited established high- ecosystem is important for anyone considering startups as a tech companies, startups, and venture-capital firms, including career path.” some founded or led by MIT alumni, as well as a three-year- old nonprofit organization dedicated to supporting both current Participants appreciated the chance to interact directly with and future entrepreneurs. They even stopped by the historic executives and entrepreneurs, especially those with MIT HP Garage, the one-car structure in Palo Alto where William connections. One such opportunity came during a reception Hewlett and David Packard launched their famous company. hosted by MIT alumnus Michael Cassidy (SB ’85, SM ’86, eecs.mit.edu 2017 CONNECTOR features 19 aerospace engineering), a serial entrepreneur, Google Vannevar Bush Professor of Electrical Engineering vice president, and project leader on GoogleX Project Loon and Computer Science; EECS Administrative Officer Mary (“balloon-powered Internet for everyone”). More than 200 Ellen Sinkus; and EECS Program Coordinator Myung-Hee people attended the event and heard StartMIT participants Vabulas. Also on the trip was Jinane Abounadi, executive present their ideas. “One important takeaway for me was director of MIT’s Sandbox Innovation Fund Program, which how willing alumni are to listen to pitches and offer feedback,” provides seed funding, mentoring, and other support for Moll said. student-initiated ventures.

For junior Ihssan Tiwani, a group session with Dropbox Melody Cao, a graduate student in EECS, said she would highly co-founder Drew Houston ’05 was a trip highlight. “It was so recommend the trip to future StartMIT participants, adding: casual that it felt like we were getting candid advice from an “You will get a ton of first-hand insight from stepping out of upperclassman at MIT who really cared about our success the academic bubble” and into the entrepreneurial ecosystem. and understood the experiences we were going through as Tiwani agreed. “It’s a free trip to the Bay Area in which you MIT students,” said Tiwani, who is double-majoring in meet some of the most accomplished and smartest MIT computer science and engineering (6-3) and economics. alums,” he said. “How could anyone possibly say ‘no’ to that?”

Tiwani also found value in reconnecting with IAP classmates during the trip. “It was nice to get updates on the latest things they are working on and the problems they are facing in “The IAP class gave me a chance to launching their new ventures,” he said. “I think it also solidified our friendship, making us feel like we are part of a community start looking at possible startup of entrepreneurs at MIT.” paths. The trip was a good incentive In San Francisco, in addition to Dropbox, the group visited Cisco to continue. Understanding the Bay Meraki, CodeFights, Lemnos Labs, the Nasdaq Entrepreneurial Center, and Thunkable. In Silicon Valley, participants visited Area ecosystem is important for Andreessen Horowitz, Apple, GoDaddy, and Lightspeed anyone considering startups.” Venture Partners. Accompanying the group were StartMIT lead organizer Anantha Chandrakasan, EECS department head and —Oscar Moll, PhD Candidate, EECS

The StartMIT group also visited Cisco Meraki, a cloud networking company, along with several other major technology companies in San Francisco and Silicon Valley.

20 features CONNECTOR 2017 eecs.mit.edu Photo: Courtesy of The Engine

Members of The Engine’s Board of Directors and Investment Advisory Committee at The Engine headquarters in Central Square (from left to right): Katie Rae, Robert Kraft, Israel Ruiz, Anantha Chandrakasan, Linda Pizzuti Henry, Amir Nashat, Sue Siegel, David Fialkow, Jeremy Wertheimer, Brad Powell, Felipe Chico, and Jonathan Kraft THE ENGINE: UP AND RUNNING With funding secured and leadership in place, MIT’s new accelerator is now focusing on selecting its first investments.

n April 2017, MIT’s new startup accelerator The Engine “From the beginning, our vision for The Engine has been to Iclosed its first investment fund for more than $150 million. foster the success of ‘tough-tech’ startups with great potential That sum will support startups developing breakthrough for positive impact for humanity,” MIT President L. Rafael Reif scientific and technological innovations with potential for said in April. “By enabling crucial investments in The Engine’s societal impact. first portfolio of companies, the funds announced today will also strengthen the local innovation ecosystem and the That was just the latest milestone for The Engine, which regional economy.” combines an accelerator, an open network of technical facilities, and a fund, which together will provide startups with Of the total capital raised for the fund — officially named The stable financial support and access to costly resources. The Engine Accelerator Fund I, L.P. — MIT invested $25 million. The initiative will focus on startups developing “tough” technologies remainder came from a small group of investors aligned with — breakthrough ideas that require time to commercialize — in the fund’s mission. sectors such as robotics, manufacturing, health technology, biotechnology, and energy. eecs.mit.edu 2017 CONNECTOR features 21 The Engine was unveiled at a high-profile launch event in October 2016. At that time, Reif described the underlying EECS Introduces New, reasons for the initiative: “If we hope for serious solutions More Flexible, Undergraduate to the world’s great challenges, we need to make sure the innovators working on those problems see a realistic pathway Curriculum to the marketplace,” he said. “The Engine can provide that pathway by prioritizing breakthrough ideas over early profit, helping to shorten the time it takes these startups to become MIT’s Department of Electrical Engineering and Computer Science (EECS) unveiled a new undergraduate curriculum ‘VC-ready,’ providing comprehensive support in the meantime, for 2016–17, and the first year has gone very smoothly, says and creating an enthusiastic community of inventors and EECS Undergraduate Officer Chris Terman. supporters who share a focus on making a better world.” The new degree requirements, which apply to students in In February 2017, The Engine named Katie Rae, a veteran the Class of 2020 and beyond, are designed to: technology entrepreneur and investor, as its president and CEO and as managing partner of its first investment fund. The • enable majors to engage earlier with core EECS material Engine also announced membership of its board of directors by cutting back the introductory requirement and investment advisory committee. • serve students with a broader range of backgrounds by Among The Engine’s inaugural board members is Anantha making a smoother introduction to software Chandrakasan, head of the Department of Electrical • allow more flexibility within the curriculum Engineering and Computer Science (EECS) and the Vannevar Bush Professor of Electrical Engineering and Computer • sharpen the specification of Laboratory and Advanced Science. Chandrakasan also headed up MIT’s Engine Working Undergraduate Subjects requirements, and Groups, which consisted of faculty, postdocs, students, and staff with specialized expertise. The groups were charged with • improve the major-project experience for students and helping guide development of Engine-related policies and faculty. procedures in areas such as technology licensing and facilities access, among others. “The new curriculum puts more choice in students’ hands, while providing a solid grounding in the essential elements of an education in electrical engineering and computer science,” EECS department head Anantha Chandrakasan, “If we hope for serious the Vannevar Bush Professor of Electrical Engineering and solutions to the world’s Computer Science, said in announcing the change last year. Students in the classes of 2017, 2018, and 2019 could choose to continue using the old requirements or great challenges, we need switch to the new requirements in fall 2016. Of the 1,580 undergraduate majors and master’s of engineering (MEng) to make sure innovators students in the department’s database, 572 have chosen the new program, and 1,008 have remained in the old program, Terman says: “Upperclassmen are allowed to working on those prob- switch, but, of course, seniors and MEng students who are close to finishing under the old program would probably not lems see a realistic path- find switching to their advantage.”

Key changes to the curriculum include reducing the way to the marketplace.” number of introductory subjects and math foundation courses from two each to one each. The new program also —MIT President L. Rafael Reif adds two elective subjects to the 6-1 (Electrical Science and Engineering) and 6-2 (Electrical Engineering and Computer Science) majors, and one elective subject to Closing The Engine’s first fund so soon after its public the 6-3 (Computer Science and Engineering) major. The 6-7 (Computer Science and Molecular Biology) major announcement shows great promise, noted Rae, who requirements were revised to refer to the next generation previously served as managing director of the popular startup of software and biology subjects, but the overall scope of accelerator Techstars Boston. “There is strong interest, and the 6-7 major is unchanged, Terman says. people are bullish on what’s coming out of MIT and Boston. We’re looking for startups with breakout technologies and Going forward, two department committees — one for great founding teams that want to build their companies in electrical engineering and one for computer science — are the New England region,” she said. With funding secured considering additional new subjects at the foundation and and leadership established, The Engine is now focusing on header levels. “I think we’ll see these courses start to selecting its first group of investments. appear in the coming academic year,” Terman says. For more information on the new undergraduate curriculum, For more about The Engine, visit engine.xyz visit eecs.mit.edu/curriculum2016

22 features CONNECTOR 2017 eecs.mit.edu MASTER- WORKS AND EECSCON: SHOWCASING STUDENTS’ WORK

April 18, 2017, was a day to talk, think, and learn about Photos: Gretchen Ertl student research.

ore than 60 undergraduates spoke or gave poster Mpresentations during EECScon, the annual undergraduate research conference sponsored by the Department of Electrical Engineering and Computer Science (EECS) and MIT Lincoln Labs. About 45 students presented posters or demonstrations during Masterworks, the annual EECS celebration of thesis research leading to the master of science (SM) and master of engineering (MEng) degrees.

Dozens of other students, faculty members, and industry guests joined the back-to-back events on April 18 to learn about students’ work (and enjoy a free lunch during EECScon and an ice-cream buffet during Masterworks). Both events featured prizes for the best presentations. EECScon winners received cash prizes of $50 to $200, while Masterworks winners received prizes donated from Apple and Samsung.

For more photos and a full list of winners, visit eecs.mit.edu

eecs.mit.edu 2017 CONNECTOR features 23 24 features CONNECTOR 2017 eecs.mit.edu RESEARCH UPDATES

Michael Carbin: Verifying Application-Specific Fault Tolerance via First-Class Fault Models 26

Stefanie Mueller: Interacting with Personal Fabrication Machines 29

Devavrat Shah: Social Data Processing 32

Max Shulaker: Next-Generation Nanosystems Q & A 35 low-overhead application- specific detection and correct VERIFYING schemes.

A major aspect of the design APPLICATION- of such mechanisms is the trade-off between the overhead (in performance, SPECIFIC FAULT memory consumption, and energy consumption) of these techniques, the frequency and TOLERANCE VIA distribution of hardware faults, and the coverage of a specific error-detection and correction scheme. For example, standard methods for DMR duplicate FIRST-CLASS the entire execution of a computation and check if the two executions of the computation agree on their results. This technique introduces significant computational and FAULT MODELS energy overhead.

Convergence By Michael Carbin, Jamieson Career Development Assistant 3000 Professor of Electrical Engineering and Computer Science; Member, Computer Science and Artificial Intelligence 2500 Laboratory (CSAIL)

2000

ue to the aggressive scaling of technology sizes in modern e from solution e from 1500 reliable Dcomputer processor fabrication, modern processors have relaxed become more vulnerable to errors that result from natural variations in processor manufacturing, natural variations 1000 in transistor reliability as processors physically age over Euclidean distanc time, and natural variations in these processors’ operating 500 environments (e.g., temperature variation and cosmic/ environmental radiation). 0 0500010000 15000 20000 25000 Large distributed systems composed of these processors Iteration — such as emerging designs for exascale supercomputers Figure 1: Reliable versus Unreliable Execution of Jacobi Iterative — are anticipated to encounter errors frequently enough that Method for Oil traditional techniques for building high-reliability applications will be too resource-intensive (in terms of time, storage, and In contrast, algorithm-based fault-tolerance techniques energy consumption) to be practical. Applications will, instead, — such as those for linear algebra — produce lightweight need to be architected to execute through errors[1]. checksums that can be used to validate whether the computation produced the correct results. For some Traditional Fault Tolerance applications, these checksums are exact, enabling the exact error detection of capabilities of DMR with lower overhead. Researchers have long sought methods to enable reliable However, for other applications, these checksums either computation on unreliable computing substrates. For are not known to exist or, at best, compromise on their example, in the 1950s, vacuum-tube-based computing error coverage. systems experienced vacuum-tube failures as frequently as every 8 hours[2]. In response, the industrial and academic Application-Specific Fault Tolerance community sought to resolve this issue both by designing more reliable computing substrates (modern CMOS transistors) Modern large computing systems have begun to operate a point and by designing fault-tolerance mechanisms. Of these latter in the trade-off space between performance/energy and error techniques, popular methods include: rates that traditional, application-oblivious fault-tolerance techniques are too resource-intensive to deploy at scale for 1) n-modular redundancy to implement majority voting large numerical computation. In response, researchers have (where n > 2), begun to expand on historical results for algorithm-based fault tolerance — alternatively, application-specific fault tolerance 2) dual-modular (2-modular) redundancy (DMR) to — to identify new opportunities for low-overhead mechanisms enable error detection and subsequent restart, and that can steer an application’s execution to produce acceptable results: that is, results that are within some tolerance of the 3) algorithm-based fault-tolerance methods to provide result expected from a fully reliable execution.

26 research CONNECTOR 2017 eecs.mit.edu Such techniques include selective n-modular redundancy in which a developer either manually or with the support of a fault-injection tool identifies instructions or regions of code that do not need to be protected for the application to produce an acceptable result, as determined by an empirical evaluation. Another class of techniques are fault-tolerant algorithms Figure 2: Leto Fault Model Specification that, through the addition of algorithm-specific checking and correction code, are tolerant to faults.

For example, Figure 1 shows the results of executing a self- in a program, Leto dynamically makes a non-deterministic stabilizing iterative solver (Jacobi iterative method) for a choice between the set of operation implementations that system of linear equations that corresponds to an oil reservoir are currently enabled in the model as indicated by their simulation problem. The graph presents the norm of the error guards evaluating to true. Namely, an operation’s guard is the of the solution vector (y-axis) as a function of the number optionally specified boolean expression that occurs after the of iterations (x-axis) for a reliable execution (in blue) and an when keyword. For these two versions of addition, the unreliable execution (in red) that encounters a fault on iteration reliable version is always enabled and the unreliable version 10,000. The unreliable execution eventually converges to the is enabled only if upset — indicating that a fault has yet to correct solution. Moreover, it recovers quickly relative to the occur in the program. algorithm’s overall convergence from a solution vector of similar error (as evidenced by previous iterations). Relational Verification: Verifying an application that has been protected with an application-specific fault-tolerance While these techniques and algorithms are promising, a major mechanism typically requires reasoning about two types of barrier to implementing either of these techniques is that their properties of the resulting application: safety properties and results either rely on empirical guarantees or — for algorithm- accuracy properties. specific techniques — hinge on the assumption that the fault model of the underlying computing substrate matches the Safety properties are standard properties of the execution of modeling assumptions of the algorithmic formalization. the application that must be true of a single execution of the application. Such properties include, for example, memory Verifying Application-Specific Fault Tolerance with Leto safety and the assertion that the application returns results that are within some range. For example, a computation that In our recent research, Brett Boston and I have developed computes a distance metric must, regardless of the accuracy Leto[3], a verification system that supports reasoning about of its results, return a value that is non-negative. In Leto, unreliably executed programs. Leto enables a developer to a developer specifies safety properties with the standard build confidence in an application-specific fault-tolerance assertion statement, assert e, as typically seen in verification mechanism by 1) enabling a developer to programmatically systems. For example, to assert that the result of a distance specify the behavior of the computing substrate’s fault model metric is non-negative, a developer may write in the program and 2) enabling a developer to verify relational assertions that the statement assert 0 <= x, where x is the result of the metric. relate the behavior of the unreliably executed program to that of a reliable execution. Accuracy properties are properties of the unreliable or relaxed execution of the application that relate its behavior and results Leto enables a developer to specify the behavior of the to that of a reliably executed version. Accuracy properties are underlying hardware system as a program that Leto relational in that they relate values of the state of the program automatically weaves into the execution of the main program. between its two semantic interpretations. For example, the In addition, Leto enables a developer to specify relational assertion -epsilon < x - x < epsilon in Leto specifies assertions that, for example, constrain the difference in results that the difference in value of x between the program’s reliable of the unreliable execution of the program from that of its execution (denoted by x) and relaxed execution (denoted by reliable execution. x) is at most epsilon.

First-Class Fault Models: Leto enables a developer to Key Insights: Leto relies on an Asymmetric Relational Hoare programmatically specify a stateful fault model. For example, Logic[4] as its core program logic. Relational Hoare Logics are a common fault model that application developers use is the a variant of the standard Hoare Logic that natively refer to the single-event-upset model. In this model, at most one fault can values of variables between two executions of the program. occur during the execution of the program. While simple, this Leto’s use of a relational program logic serves two goals: 1) model can capture real fault models in which it is possible for it gives a semantics to accuracy properties and 2) it enables errors to happen during execution, but with small probability. tractable verification of safety properties.

Figure 2 presents a specification in Leto of a single-event As an example of the latter, proving the memory safety of an upset model that affects only addition operations. This model application outright can be challenging for many applications. includes a boolean valued state variable that records whether However, application-specific fault-tolerance mechanisms can a fault has occurred during the execution of the program. The typically be designed and deployed such that it is possible to model then exports two versions of the addition operator. Line verify that for any given array access or memory access, errors 4 specifies the reliable implementation of addition, while Line in the application do not interfere with the accessed address. 6 specifies an unreliable version. For each addition operation Such properties are typically easier to verify for a protected eecs.mit.edu 2017 CONNECTOR research 27 application than verifying the safety of the memory access outright.

Leto therefore enables developers to tractably verify a strong relative safety guarantee: if the original application satisfies all of the specified safety properties, then relaxed executions of the application with its deployed application-specific fault- tolerance mechanisms also satisfy these safety properties.

Results: We have used Leto to verify key correctness properties on several self-stabilizing algorithms: Jacobi, Self- stabilizing Conjugate Gradient, and Self-stabilizing Steepest Descent. Our results show that is possible to verify the key invariants required to prove that these algorithms’ self-stability guarantees hold for their implementations. In general, Leto enables developers to specify and verify the rich fault-aware properties seen in applications with application-specific fault- tolerance mechanisms.

Future Approximate Computing Systems

As we continue to scale the size of our systems to include larger collections of increasingly less reliable components, our methods for architecting software systems will need scalable and verifiable methods to manage the uncertainty in the underlying execution substrates of the systems. Leto, along with other work in my Programming Systems Group[5, 6, 7], directly provides new programming languages, methodologies, and systems that enable developers to reason about unreliable, continuous, and probabilistic computation.

References

[1] S. Amarasinghe, et al. ExaScale Software Study: Software Challenges in Extreme Scale Systems. DARPA IPTO, Air Force Research Labs, Technical Report (2009).

[2] J. Von Neumann. Probabilistic Logics and the Synthesis of Reliable Organisms from Unreliable Components. Automata Studies, 35 (1956).

[3] B. Boston and M. Carbin. Verifying Application-Specific Fault Tolerance via First-Class Models. In submission.

[4] M. Carbin, D. Kim, S. Misailovic, and M. Rinard. Proving Acceptability Properties of Relaxed Nondeterminisic Approximate Programs. PLDI (2012).

[5] E. Atkinson and M. Carbin. Towards Correct-by- Construction Probabilistic Inference. NIPS Workshop on Machine Learning Systems (2016).

[6] E. Atkinson and M. Carbin. Towards Typesafety to Explicitly- Coded Probabilistic Inference Procedures. In submission.

[7] B. Sherman, L. Sciarappa, M. Carbin, and A. Chlipala. Overlapping Pattern Matching for Programming with Continuous Functions. In preparation.

28 research CONNECTOR 2017 eecs.mit.edu Similar to 3D printers today, early computers were limited INTERACTING to expert users because when programs were executed in one go overnight, users had to WITH PERSONAL know what they were doing to FABRICATION succeed. 1.3 Towards Turn-Taking and MACHINES Direct Manipulation However, today we are at a point at which even non-technical users can use personal By Stefanie Mueller, X-Consortium Career Development computers. Beside many technical developments, two Assistant Professor of Electrical Engineering and Computer advances in the interaction model enabled this: (1) the move Science; Member, Computer Science and Artificial Intelligence from executing in one go to turn-taking, and (2) the move from Laboratory (CSAIL) turn-taking to direct manipulation[3].

1) Turn-taking: By decreasing the interaction unit to single ersonal fabrication tools, such as 3D printers, are on the requests, turn-taking systems, such as the command line, Pway to enabling a future in which non-technical users will provided users with feedback after every input. This enabled be able to create custom objects. With the recent drop in price the trial-and-error process that non-technical users tend for 3D printing hardware, these tools are about to enter the to employ: quickly iterating through potential solutions and mass market: While the average consumer 3D printer was building each step onto the results of previous ones[2]. priced at $14,000 in 2007, today’s hardware costs, on average, However, while the turn-taking interaction model provided only $500[10]. Given the decreasing price, it is not surprising a great step forward to making the technology available for that the number of consumer 3D printers sold has doubled non-technical users, the feedback cycle was still limited in that every year[10]. it consisted of two discrete steps: users first had to create an input and only afterwards received feedback. While the hardware is now affordable and the number of people who own a 3D printer is increasing, only a few users actually 2) Direct manipulation: With the invention of direct create new 3D models. Most download models from a platform, manipulation[9] that further decreased the interaction unit to a such as Thingiverse, and fabricate them on their 3D printers. single feature, users finally received real-time feedback: Input At most, users adjust a few parameters of the model, such as by the user and output by the system are so tightly coupled changing its color or browsing between predetermined shape that no visible lag exists. This tightened feedback cycle has options. many benefits, among others that “novices can learn basic functionality quickly” and “retain operational concepts”[8]. I believe that personal fabrication has the potential for more: I (See Figure 1.) envision a future in which, rather than just consuming existing content, 3D printers will allow non-technical users to create objects that only trained experts can create today. While there are many open challenges, I will use this article to discuss how we can improve the interaction model underlying current fabrication devices.

1.1 Interaction Model with 3D Printers Today

In the current interaction model, users sit at a computer and use a digital 3D editor to create a digital 3D model. Only at the end of the design process do users send the file to the 3D printer, which creates the object in one go. Because 3D printing is slow, this process tends to take hours of printing time for small objects and may even require overnight printing.

1.2 Drawing a Parallel to Personal Computing

Looking back in history, this interaction model with the delayed feedback was also common with early computers[1]. In the early ’60s, computers were so slow that the average program had to be executed overnight. Feedback was delayed until the next morning and if a program failed, users had to repeat the entire process, potentially waiting another night for results. Figure 1 eecs.mit.edu 2017 CONNECTOR research 29 Figure 1. Server Feedback Figure 2: constructable

As described above, the current interaction model of 3D While constructable allows for fast physical feedback, the printers requires objects to be fabricated in one go. Thus, interaction is still best described as turn-taking because it from a human-computer interaction standpoint, we are today consists of two discrete steps: users first perform a command at the point at which we were with personal computers in the and then the system responds with physical feedback. 1960s: Only few users are able to use the technology, and even for experts, it is a cumbersome process due to the delayed 2) Direct Manipulation: Continuous Forming. By decreasing feedback. the interaction unit even further to a single feature, we explore how to make the workpiece change while the user is 1.4 Bringing Direct Manipulation to Fabrication manipulating it, resulting in real-time physical feedback: Input by the user and output by the fabrication device are so tightly I argue that by repeating the evolution of the interaction model coupled that no visible lag exists. Our system FormFab[7] from personal computing, we will see the same benefits for provides such continuous physical feedback (see Figure 3). To personal fabrication: Direct manipulation will allow non- accomplish this, FormFab neither adds nor subtracts material, technical users to create physical objects as easily as they but instead reshapes it (formative fabrication). A heat gun manipulate digital data with today’s personal computers. attached to a robotic arm warms up a thermoplastic sheet until it becomes compliant; users then control a pneumatic system A direct manipulation system for personal fabrication needs that applies either pressure or vacuum, thereby pushing the to have four main characteristics: 1) the physical environment material outwards or pulling it inwards. As users interact, they is the workspace, not a digital editor; 2) users work hands-on see the workpiece change continuously. on the physical workpiece through physical tools as known from traditional crafting; 3) each physical action results in immediate physical change, which can also be reversed; and 4) in contrast to traditional crafting, users receive support from a computer system that helps to achieve precision.

In the following section, we show examples of two systems that implement the requirements listed above and iteratively decrease the interaction unit from entire objects, to single elements, to features to achieve real-time physical feedback.

1) Turn-taking: Interactive Laser-Cutting. To illustrate what a turn-taking system for personal fabrication might look like, we decrease the interaction unit from entire objects to single elements. In our system constructable[6], users draw with a laser pointer onto the workpiece inside a laser cutter. The drawing is captured with a camera. As soon as the user finishes drawing an element, such as a line, the constructable system beautifies the path and cuts it, resulting in physical output after every editing step. Different tools allow users to accomplish different tasks, such as copy-pasting physical shapes or creating matching finger joints between two edges. In addition, constructable ensures that all physical output is aligned (see Figure 2). Figure 3

“I envision a future in which, rather than just consuming existing content, 3D printers will allow non-technical users to create objects that only trained experts can create today.” Figure 2

30 research CONNECTOR 2017 eecs.mit.edu 1.5 Discussion References

Direct manipulation systems for personal fabrication extend [1] P. Ceruzzi, A History of Modern Computing, 2nd edition. the range of problems novice users can tackle, but they The MIT Press (2003). are subject to the same limitations as those for personal computing: While they are useful for some design problems, [2] M. Csikszentmihalyi, Flow: The Psychology of Optimal they are less so for others. As Norman et al.[4] point out, direct Experience. Harper Perennial Modern Classics (1990). manipulation interfaces are limited to operations that can be done on “visible objects” and have “difficulties handling [3] J. Grudin, A Moving Target: The Evolution of Human- variables” and “distinguishing an individual element from a Computer Interaction. Human-Computer Interaction representation of a set or class of elements.” Thus design Handbook, 3rd edition, Taylor and Francis (2012). problems that require more abstract thinking for which users must first sit down with a piece of paper and make a [4] E. Hutchins, J. Hollan, and D. Norman. Direct Manipulation detailed plan are better handled with traditional digital 3D Interfaces. Human-Computer-Interaction (1985), vol. 1, pp. editing. In addition, the systems presented in this article 311-338. inherently scale 1:1 and do not offer a way of inspecting a detail in magnification, which limits users to projects that fit a [5] Moore’s law for 3D printing: https://3dprint.com/7543/ particular scale. The same way that a saw and a wood chisel 3d-printing-moores-law cannot replace a detailed design process, our systems cannot replace a complex 3D editing tool for trained engineers. [6] S. Mueller, P. Lopes, P. Baudisch. Interactive Construction: Interactive Fabrication of Functional Mechanical Devices. 1.6 Outlook Proceedings of the ACM UIST 2012, pp. 599-606.

We focused on using technology available today to explore [7] S. Mueller, A. Seufert, H. Peng, R. Kovacs, K. Reuss, T. interaction paradigms that will become possible in the future Wollowski, F. Guimbetiere, P. Baudisch. Continuous Interactive when fabrication actually gets faster. In recent years, we have Fabrication. Under review for ACM UIST 2017. begun rapidly advancing towards such a future. The recently introduced 3D printer Carbon3D, for instance, speeds up [8] B. Shneiderman. Direct Manipulation: A Step Beyond fabrication by up to 200 times. Programming Languages. Computer (1983), vol. 16, issue 8, pp. 57-69. While there is little data today that could prove a Moore’s law for 3D printers, an executive from 3D Systems, a leading [9] B. Shneiderman. The Future of Interactive Systems and manufacturer, noted in 2014 that 3D printing speed had, the Emergence of Direct Manipulation. Proceedings of the on average, doubled every 24 months over the previous 10 NYU Symposium on User Interfaces on Human Factors and years[5]. If such a trend should materialize, it is not far-fetched Interactive Computer Systems (1984), pp. 1–28. to assume that fabrication technology will be able to provide feedback even for large high-resolution objects within seconds [10] Wohlers Report (2016). https://wohlersassociates.com/ or even in real time, thereby enabling a future in which digital 2016report.htm displays will be replaced with physical displays that transform virtual reality into actual physical reality.

“By repeating the evolution of the interaction model from personal computing, we will see the same benefits for personal fabrication: direct manipulation will allow non-technical users to create physical objects as easily as they manipulate digital data with today’s personal computers.”

eecs.mit.edu 2017 CONNECTOR research 31 In short, the key intellectual challenge is in finding a SOCIAL DATA sufficiently flexible model for social data that is both statistically and computationally PROCESSING tractable. This is a major challenge, and its successful By Devavrat Shah, Professor of Electrical Engineering and resolution can have substantial Computer Science; Member, Laboratory for Information and impact on all the previously Decision Sciences (LIDS), Institute for Data, System and Society mentioned scenarios — and (IDSS); Director, Statistics and Data Science Center (SDSC) many others.

Turning Weakness to Strength. To progress toward such a ackground. What went wrong with the election polls in the grand challenge, it is essential to identify the properties of 2016 U.S. presidential election? How can the online activity B social data that are ubiquitous across a variety of scenarios and of the population help curate better life experiences for all? that can be captured to develop meaningful models. Can we utilize online personas for reaching out to individuals in a targeted manner? What about predicting the demand for We have identified one such property: social data is (or should espadrilles this summer? Or ranking the performance of your be) anonymous. That is, from the data-processing perspective, favorite sports team? And what happened to the promise of it should not matter who has generated the data. To put it using collective wisdom for stopping the spread of ‘’fake news’’ another way, the overall conclusion should remain invariant on Facebook? if we re-name the individuals who have generated the data. For example, the results of a democratic election should not Answers to all those questions depend on our ability to process change even if the voters’ names change, as long as the total “social” data to extract meaningful information. For the past number of votes for each candidate remains the same. In the few decades, and even more so recently, everything online is same way, the popularity of a specific style of espadrilles does being recorded. If aliens came to earth and inspected the social not depend on which specific individuals bought them, only on data — generated by us as a society (not by machines) — they how many pairs are being purchased. would learn, for instance, that Patriots’ Day is when the Boston Marathon is held. Anonymity seems like a constraint or a weakness from any angle you look at it. Put another way: Social data presents us with an enormous opportunity for making data-driven decisions for better living, After all, anonymity and privacy protections restrict the type more efficient operations, more effective policy making, and of information that we can mine from data. But we derive overall uplifting of societies. Here, data is the enabler. Access strength from this apparent weakness. It will help us address to social data has been democratized; the key to success lies the challenge of developing tractable and flexible models for in the ability to process it so that we can extract meaningful social data. information from it. This makes it feasible for someone like me as an “ivory-tower” academic to carefully think through Mathematically, anonymity can be viewed as the underlying a solution, test it out, and then have a chance of making an “probabilistic model” having a certain “exchangeability” impact in the real world — and, in the process, advance the property. A remarkable development in mathematical foundations of statistics and machine learning. In that sense, statistics, starting with the work of de Finetti in the 1930s with social-data processing presents an unusual, potentially once- further developments in the 1970s and 1980s, provides a crisp in-a-generational, opportunity that can lead to a remarkable non-parametric characterization for such models: the Latent convergence of academia and industry. Variable Model. We utilize the Latent Variable Model for social- data processing for a variety of scenarios, including some of Challenge. The standard approach for data-driven decisions those discussed in the questions that opened this article. following statistical decision theory is to use an appropriate model that connects data to decision variables, helps make Taking the First Steps. We start by examining the question desired predictions, and eventually facilitates optimization of designing personalization or recommendation systems over decision choices. Here, data is generated by humans, so such as those used by Netflix, YouTube, Amazon, and Spotify. modeling social behavioral aspects is essential. Any social Here, the goal is using the history of an entire population’s scientist can attest that modeling human behavior is an preferences to predict which movies, music, books, or other extremely intricate task and the resulting models can be highly products that individual consumers may like and that they context-dependent. That makes it especially challenging to have not already experienced. On one hand, the question is: come up with effective, meaningful models. The only hope is What is the best algorithm to design for that end goal using the for gaining access to lots of social data to decipher the right non-parametric model emerging from exchangeability? On the model for a particular interest from a large class of models. In other hand, that question has been with us since the dawn of other words, we need a model that is flexible enough to capture the e-commerce era. a wide array of social scenarios. But the model must be sufficiently tractable so that with enough data it can capture the ground truth faithfully, and it is important that such a system There is a popular algorithm, called Collaborative Filtering[0], can computationally scale along with the data. that has been with us from the start and that continues to be used due to its simplicity and empirical success. In a nutshell,

32 research CONNECTOR 2017 eecs.mit.edu the algorithm embodies the following time-tested insight: (b) finding accurate answers to questions such as those If your friend likes a new movie, and that friend’s tastes are collected through polls and surveys or crowd-sourcing similar to your own, you will likely enjoy the new movie as well. platforms based on noisy answers[4]; and Such a simple, intuitive — or, may I say, social — algorithm has been used in practice successfully but with little understanding (c) finding ommunitiesc in a society based on noisy pair-wise of why it works. Ultimately, the goal is to understand the interaction data[5]. Collaborative Filtering algorithm and, in the process, try to find ways to improve it — and, if feasible, achieve the best It turns out that for each of these scenarios (and more), the performance. Latent Variable Model is a less restrictive, or more flexible, model while being tractable. Subsequently, this provides a way In our work[1], we have precisely addressed this question. We to develop a data-processing algorithm for a wide variety of use the non-parametric model arising from exchangeability social settings simultaneously. For example, I am very excited to study this question. We find that the Collaborative Filtering about our ongoing project, where we use the Latent Variable algorithm, somewhat miraculously, is solving the right Model for time-series data in high-dimension for accurate statistical problem. In a nutshell, it implicitly performs forecasting in real time. “local’’ approximation for the non-parametric functional model underlying the data without knowing the function! The The Latent Variable Model has applicability beyond social nature of the algorithm leads to accurate learning when the data (cf. see [1] and [2]). For example, it can help de-noise available data is sufficient enough. However, this is not the image data by viewing images as 3-order tensor of RGB “best” performance in terms of the data required for accurate values and connecting to a Latent Variable Model. An example learning. of the efficacy of the Collaborative Filtering algorithm for de- noising image over academic benchmark images is described The above framework provides systematic means to improve in Figure 2. upon the Collaborative Filtering algorithm. To begin with, in the regime where a lot of data is available, a simple improvement Summary. Social data presents us with a tremendous to the Collaborative Filtering algorithm can lead to superior opportunity. To realize the opportunity, it is essential to develop performance (see Figure 1). This improved algorithm has the statistical models “universal’’ enough to faithfully capture a best-known performance for the most generic model class as broad class of “social” scenarios; and inference algorithms argued in[1]. for such models that are statistically and computationally tractable. This is a grand challenge, because modeling social A well-known limitation of the Collaborative Filtering algorithm behavior that generates data is extremely hard. The non- in practice is its inability to work well in the presence of very parametric Latent Variable Model naturally arising due to the sparse data. Imagine the scenario of YouTube where 300 hours anonymity property of social data is a promising candidate in of video are uploaded every minute, or a shoe retailer where making progress towards this challenge, especially given the completely new designs of espadrilles are introduced every initial progress made. season. There is very little data about new shows or espadrilles across the population. In the context of Collaborative Filtering, you may find that none of your friends has watched the new shows or tried the new espadrilles. Therefore, the algorithm may not able to provide meaningful recommendations.

In a recent work[2], we extend the Collaborative Filtering algorithm to overcome this sparse data limitation by using the following “social insight’’ guided by the non-parametric statistical model: your friend’s friend can be your friend; or more generally, if you and your friend have similar preferences, and your friend’s friend has similar preferences to your friend, then your friend’s friend may have preferences similar to yours. The resulting “iterative’’ Collaborative Filtering algorithm turns out to have (near) optimal statistical performance in sparse data regime. And it’s remarkably simple.

Where to Go from Here. The non-parametric Latent Variable model is useful beyond the setting of recommendation or personalization. Over the past decade, as a community, we Figure 1. This is an experiment representing the performance of various have developed solutions for a variety of scenarios. Notable recommendation algorithms using the MovieLens dataset. The performance ones include: of the algorithm is measured in Root-Mean-Squared-Error (RMSE) — the lower, the better. Algorithm performance is evaluated for different fractions (a) finding aggregate ranking over a collection of choices such of test data (the rest of the data is training). The orange curve corresponds to spectral method (soft-impute), the blue curve corresponds to user-user as teams, players, or faculty candidates by synthesizing data variant of Collaborative Filtering, the red curve corresponds to item-item available in the form of partial rankings or preferences such variant of Collaborative Filtering, and the purple curve corresponds to the as pair-wise comparisons[3]; improved Collaborative Filtering algorithm using the Latent Variable Model.

eecs.mit.edu 2017 CONNECTOR research 33 Figure 2. Recovery results for two images (building facade and peppers) with 70 percent of missing entries under different algorithms are presented. The last column corresponds to our algorithm, which is based on Collaborative Filtering. The performance is measured with respect to Relative Squared Error (RSE) — again, the lower, the better.

References

[0] D. Goldberg, D. Nichols, B.M. Oki, and D. Terry. Using Collaborative Filtering to Weave an Information Tapestry. Communications of ACM, 1992.

[1] C. Lee, Y. Li, D. Shah, and D. Song. Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering. Proceedings of the 30th Conference on Neural Information Processing Systems (NIPS), 2016.

[2] C. Borgs, J. Chayes, C. Lee, and D. Shah. Recommendations for Sparse Datasets via Similarity Based Collaborative Filtering. Preprint, 2017.

[3] S. Negahban, S. Oh, and D. Shah. Rank Centrality: Ranking from Pair-wise Comparisons, Operations Research, 2016. Preliminary version in Proceedings of NIPS, 2012.

[4] D. Karger, S. Oh, and D. Shah. Budget-Optimal Task Allocation for Reliable Crowd-Sourcing, Operations Research, 2014. Preliminary version in Proceedings of NIPS, 2011.

[5] C. Moore. Computer Science and Physics of Community Detection: Landscapes, Phase Transitions and Hardness, Bulletin of EATCS, 2017.

“ Social data presents us with an enormous opportunity for making data-driven decisions for better living, more efficient operations, more effective policy making, and overall uplifting of societies.”

34 research CONNECTOR 2017 eecs.mit.edu NEXT-GENERATION NANOSYSTEMS: A Q & A WITH MAX SHULAKER

By Anne Stuart | EECS

ax Shulaker, an expert on nanosystems exploiting The more things I did in the lab, the more excited I became Memerging nanotechnologies, joined the EECS faculty in the about the technologies. That’s one reason I always encourage fall of 2016. He is the Emmanuel E. Landsman (1958) Career undergraduates to get involved in research — you never know Development Assistant Professor of Electrical Engineering when you will find your passion. and Computer Science and a principal investigator for both the Microsystems Technology Laboratories (MTL) and Research This work was exciting to me because it spanned all layers Laboratory of Electronics (RLE). At MIT, he is starting the Novel of the computing stack. I began focusing on the materials Electronic Systems (NOVELS) research group. and carbon nanotube synthesis. Then we started looking at circuits. Then we started looking at systems. Then we starting He received bachelor’s, master’s, and PhD degrees in electrical looking at new applications. And now, my own PhD students engineering from Stanford University. His PhD research on are working on projects that span all those layers as well. carbon nanotube-based transistors and circuits resulted in They have to work on the new materials to build new circuits to several firsts: enable new systems to demonstrate new applications.

• the first digital systems built entirely using carbon nanotube When you add up all of the benefits across all these different field-effect transistors, or FETs (including the first carbon layers, you aren’t talking about 10 or 20 percent benefits nanotube microprocessor), anymore, but instead gains exceeding several orders of magnitude. This work has the potential to make a huge • the first monolithic three-dimensional integrated circuits difference in the world, and it is why I — and my students — combining arbitrary vertical stacking of logic and memory, are so excited to be working on it. and

• the highest performance and highly-scaled carbon nanotube transistors to date. “I began focusing on the At MIT, Shulaker is launching an experimental research materials and carbon nanotube program aimed at realizing his vision for the next generation of electronic systems based on transformational nanosystems, synthesis. Then we started leveraging the unique properties of emerging nanotechnologies and nanodevices to create new systems and architectures with looking at circuits. Then we enhanced functionality and improved performance. started looking at systems. Shulaker was interviewed in his Building 39 office, which overlooks the ongoing construction for MIT.nano, the new Then we starting looking at nanoscale fabrication and characterization facility scheduled to open in 2018. He spoke about his past and current research, his new applications. And now, my new experimental program, and his early experience at MIT. own PhD students are working Q: How did you become interested in nanosystems and nanotechnologies? on projects that span all those

A: I got interested in this area in a class on digital systems layers as well.” that I took freshman or sophomore year at Stanford. The professor talked about trying to make a computer out of carbon nanotubes. It seemed like a crazy idea, but I asked the professor if I could help, and he said “yes.” That started close to a decade of working on carbon nanotubes. eecs.mit.edu 2017 CONNECTOR research 35 Q. You’ve said that the broader field of emerging simultaneously providing a rich set of enhanced functionality nanotechnologies is both exciting and depressing. for applications that otherwise may not be feasible using Can you explain? traditional technologies.” Could you talk about what you mean by the “right devices,” the “right architectures,” and A: Sure. It’s exciting because of the promise we say that by the “right way”? using these new technologies, we can make chips that will be extremely fast and extremely energy-efficient. We can have A: That’s a very important question. To take a step back: if we sensors distributed all over the world. We can have chips in want to understand how to improve computing, we have to your body finding — and curing — diseases. And although these know what are the obstacles we are facing today. And it turns promises are exciting, they’re also a little depressing, because out that part of the reason progress in computing is stalling is while we talk about how these technologies will change the there aren’t just one or two obstacles facing computing, but world, too often in the lab we only make a single device, or a many. For example, the “power wall” stems from the fact that single transistor. So there is a huge disconnect between the it is becoming increasingly difficult to shrink devices smaller, motivation that we use to drive this field of research, and what and the “memory wall” refers to how a computer today can we actually show working in the lab. spend the vast majority of its time and energy just moving data between memory and logic — and there are many more My group is trying to bridge the gap between what we say these “walls.” emerging nanotechnologies can enable and what we actually demonstrate in the lab. To do this, the group works on — out of Because there are many obstacles, it means that there cannot necessity — many different aspects: some people focus more just be one solution. For instance, even if I create an amazing on design and simulation, while others are experimentalists transistor, I would still face the memory wall, and visa-versa. and actually build the systems that we design. So to realize really, really big gains — like orders-of-magnitude gains — in computing, just solving one problem isn’t enough. Q: Tell me about your groundbreaking PhD research. How Instead, we need to use better devices to build better systems did you become interested in that subject? Did you expect to enable new applications. So device-level research cannot the number of “firsts” your research generated, or were you exist in a vacuum. When we work on new devices, we have to surprised? What’s been the result? figure out which devices, or which “right” device, is going to enable us to not only solve the “power wall,” but also enable us A: I did not know when I started undergrad that I was “meant” to build new system architectures — or the “right” system — to to do nanosystems. I got involved early in research, and tried address the memory wall. out several different areas. It was only by doing and working in the lab that I found out what I didn’t like, what I did like, and Q: Next, can you provide examples of enhanced functionality eventually, what I loved. and improved performance?

We were certainly happy to have a number of “firsts,” but A: We will have something published on this very shortly, and it that was never the motivation to doing the work. I think the is a fast-expanding thrust for our group. By leveraging the new fact that we are working to define a new area of research — fabrication techniques that some emerging nanotechnologies nanosystems — naturally makes the work new and, hopefully, afford us, we can actually make 3D chips, skyscraper chips interesting. While I found my own research during my PhD with multiple levels built one on top of the other. You can have fascinating, I’m even more excited about the projects my sensing, data storage, and computation — all in one chip. students are working on. They are doing a fantastic job, and I’m That kind of chip, with fine-grained integration between these eager to see all of the “firsts” they achieve. heterogeneous aspects of a system, can only be built using these new technologies. In fact, we are working in collaboration Q: Have you actually launched your experimental program with Stanford University on a project which shows that this is at MIT? the key to achieving the next 1,000X gain in energy efficiency.

A: Yes. I feel tremendously lucky to have formed a group Q: You’ve also been described as planning “to leverage the around an amazingly strong and talented group of core richness of new nanomaterials, new computing and memory students. I guess it is a cliché to say that the best part of being technologies, and heterogeneous integration to enable new a professor is working with students, but it really surprised applications beyond the scope of traditional computing.” me how true that has been. It’s the students in my research Please talk more about some of these new nanomaterials and group, it’s the students in my classes. Thanks in large part to technologies — and, especially, their potential. them, and thanks to the amazing amount of support I’ve gotten from MIT and other faculty here, as well as from our sponsors, A: I like to say that my group is not “married” to any specific our lab is up and running. My students are in the lab right now emerging nanomaterial or nanotechnology. Rather, we are building the next generation of these nanosystems! pretty substrate-agnostic, and instead really try to figure out which material is going to enable which devices to enable Q: Here’s something you’ve said about your work: “While which systems, and so on. That being said, since a key investigating new devices or new architectures separately can application thrust for us is computing, we do work heavily on be beneficial, combining the ‘right’ devices, with the ‘right’ carbon nanotubes, which are rolled-up sheets of graphene to architectures, in the ‘right’ way, results in performance gains form nanocylinders with diameters of only about 1 nanometer. that far exceed the sum of their individual benefits, while As you can imagine, there are a whole host of amazing things

36 research CONNECTOR 2017 eecs.mit.edu you can do with a carbon nanotube. We’ve made state-of-the- Q: Anything else you’d like to add? art, very energy-efficient transistors using them and we are beginning to use them as physical nano-sized tubes, and so on. A: Coming into MIT, I had a very clear notion of what I wanted my group to work on. But that’s been turned on its head. We have been fortunate enough to also start collaborating I’ve been so lucky to interact with other faculty here who are with other faculty here at MIT who work with other types of unbelievably talented. Together, we’ve come up with some nanomaterials, and we have been developing new systems and really cool new ideas and projects I could not have dreamed of applications leveraging those materials also. Hopefully, you’ll even describing before. be able to read about these new ideas soon! For instance, we have been so fortunate to start working Q: You’ve also been described as having the ultimate goal of today with Sangeeta Bhatia’s lab, developing new imaging driving nanosystems “from concept to reality, resulting in and diagnostic modalities, which is something very removed hardware demonstrations of what future electronic systems from traditional “computing.” [Editor’s Note: Sangeeta Bhatia, might look like.” How close are we to seeing nanosystems the John J. and Dorothy Wilson Professor at MIT’s Institute move from concept to reality? How will that happen? for Medical Engineering and Science (IMES) and in EECS, is director of the MIT Laboratory for Multiscale Regenerative A: It is actually a reality today. We can build and test these Technologies (LMRT).] futuristic nanosystems, and perform certain tasks now that you simply cannot perform with conventional hardware today. These fantastic collaborations allow us to still drive our core We have also been extremely fortunate to develop a strong competency of computing, yet simultaneously explore how collaboration with Analog Devices, Inc. — which, by the way, nanosystems can impact applications that lie beyond the scope has done a remarkable job of fostering truly innovative ideas of what we traditionally view as computing. and projects — and we are working hard to see just how far we can push these futuristic ideas into becoming reality. Editor’s Note: Shulaker was the lead author of an article about Another important aspect is that what we work on is development of a new 3-D computer chip, published in the journal compatible with what exists in fabrication and design. We can Nature in July 2017. For more on that story, see build on top of any conventional silicon chip today, using the news.mit.edu/2017/new-3-d-chip-combines-computing-and- same tools and design infrastructure that already exists. This data-storage-0705. makes the barrier to introduction much lower. Who knows? Maybe one day, we will replace all of silicon. But to begin with, we don’t need to do that.

“What we work on is compatible with what exists in fabrication and design. We can build on top of any conventional silicon chip today, using the same tools and design infrastructure that already exists. This makes the barrier to introduction much lower.”

eecs.mit.edu 2017 CONNECTOR research 37 FACULTY FOCUS

Faculty Awards 39

Faculty Research Innovation Fellowships (FRIFs) 45

New EECS Associate Department Heads 46

EECS Professorships 47

New Career Development Chairs 51

New Faculty 51

Remembering EECS Faculty: Mildred S. Dresselhaus, Robert Fano 54 Elfar Adalsteinsson Anant Agarwal Mohammed Alizadeh Frank Quick Faculty Research Padmi Shri Award Sloan Research Fellowship Innovation Fellowship Facebook Faculty Award VMWare Early Career Faculty Award Google Research Award

Hari Balakrishnan Regina Barzilay Karl Berggren American Academy of Arts and Delta Electronics Professor of Bose Fellowship Sciences Electrical Engineering and Frank Quick Faculty Research Computer Science Innovation Fellowship

Tim Berners-Lee Sangeeta Bhatia Duane Boning A.M. Turing Award, Association for National Academy of Inventors Clarence J. LeBel Professor of Computing Machinery National Academy of Science Electrical Engineering Utrecht University Honorary Doctorate

eecs.mit.edu 2017 CONNECTOR faculty 39 Tamara Broderick Anantha Chandrakasan Munther Dahleh Google Research Award UC Berkeley EE Distinguished Alumni International Federation of Automatic Savage Award Award Control (IFAC) Award ISBA Lifetime Members Junior Researchers Award

Randall Davis Erik Demaine Srini Devadas Institute for Operations Research and ACM Fellow IEEE W. Wallace McDowell Award from the Management Sciences (INFORMS) Rare Craft Fellowship Award, the IEEE Computer Society 2016 Innovative Applications of American Craft Council Analytics Award Bard College Honorary Degree

Fredo Durand Dirk Englund G. David Forney, Jr. ACM Fellow Adolph Lomb Medal, Optical Society IEEE Medal of Honor ACM Siggraph Computer Graphics Achievement Award

40 faculty CONNECTOR 2017 eecs.mit.edu William Freeman James Fujimoto Shafi Goldwasser ACM Fellow National Academy of Engineering Fritz University of Haifa Honorary Doctorate J. and Dolores H. Russ Prize Barnard College Medal of Distinction Russian Academy of Sciences Suffrage Science Award, Imperial College London

Polina Golland Jongyoon Han Ruonan Han MICCAI Society Fellow Frank Quick Faculty Research NSF CAREER Award Frank Quick Faculty Research Innovation Fellowshipp Innovation Fellowship

Thomas Heldt Tommi Jaakkola Daniel Jackson W.M. Keck Career Development Pro- Thomas Siebel Professor ACM Fellow fessor in Biomedical Engineering Association for the Advancement of Arthur C. Smith Award Louis D. Smullin (‘39) Award for Artificial Intelligence Fellow 2017 ACM SIGSOFT Outstanding Teaching Excellence Researcher

eecs.mit.edu 2017 CONNECTOR faculty 41 Stefanie Jegelka Dina Katabi Manolis Kellis Google Research Award National Academy of Engineering EECS Faculty Research Innovation Fellowship

Jae S. Lim Barbara Liskov Luqiao Liu Inducted into the Consumer NCWIT Pioneer in Tech Award NSF CAREER Award Technology Hall of Fame

Nancy Lynch Aleksander Madry Muriel Medard National Academy of Sciences Sloan Research Fellowship IEEE Vehicular Technology Society Google Research Award James Evans Avant Garde Award

42 faculty CONNECTOR 2017 eecs.mit.edu Stefanie Mueller Tomás Palacios Ronald Rivest X-Consortium Career Development IEEE Fellow Electronic Frontier Foundation Assistant Professor Pioneer Award Forbes 30 Under 30 in Science

Daniela Rus Max Shulaker Henry I. Smith American Academy of Arts and Sciences Emmanuel E. Landsman (1958) Career IEEE Robert N. Noyce Medal Engelberger Robotics Award from Development Assistant Professor Robotics Industries Association

Justin Solomon David Sontag Vivienne Sze X-Window Consortium Career Hermann L. F. von Helmholtz Career Young Investigator Research Program Development Assistant Professor Development Assistant Professor in (YIP) award from the Air Force Office Army Young Investigator Award the Institute for Medical Engineering of Scientific Research (AFOSR) Forbes 30 Under 30 in Science and Science (IMES) 3M Non-Tenured Faculty Award

eecs.mit.edu 2017 CONNECTOR faculty 43 Peter Szolovits Russell Tedrake John Tsitsiklis International Academy of Health Toyota Professor ACM SIGMETRICS Achievement Award Sciences Informatics

Antonio Torralba Caroline Uhler Cardinal Warde Frank Quick Faculty Research Sloan Research Fellowship Stevens Institute of Technology, Innovation Fellowship NSF CAREER Award Distinguished Alumni Award, Science and Technology

EECS Awards Each year, EECS honors faculty, students, and staff for their outstanding achievements.

2016 Awards: eecs.mit.edu/2016-Spring-Awards

2017 Awards: eecs.mit.edu/2017-Spring-Awards Ron Weiss Virginia Williams Bose Fellowship Steven G. (1968) and Renee Finn Career Development Associate Professor NSF CAREER Award Sloan Research Fellowship

44 faculty CONNECTOR 2017 eecs.mit.edu FACULTY RESEARCH INNOVATION FELLOWSHIPS (FRIFs)

Elfar Adalsteinsson Karl Berggren Antonio Torralba

Three professors in the Department of Electrical Engineering Karl Berggren is a professor of electrical engineering, a and Computer Science (EECS) have been awarded 2016–2017 principal investigator in the Research Laboratory of Electronics Frank Quick Faculty Research Innovation Fellowships (FRIFs). (RLE), and a core member of the Microsystems Technology Laboratory (MTL). His research focuses on methods of The FRIFs were created to recognize midcareer faculty nanofabrication, especially applied to superconductive sensors for outstanding research contributions and international and circuits, photodetectors, electronics and computing, and leadership in their fields. FRIFs provide faculty members energy systems. More specifically, current nanofabrication with resources to pursue new research and development efforts emphasize developing improved charged-particle-based paths and to make potentially important discoveries through lithography to direct self-assembly by using block copolymers early-stage research. (materials systems that self-assemble to form integrated- circuit-like patterns on the 10-nm length scale). His efforts Elfar Adalsteinsson is a professor in EECS and the Institute in the area of superconductivity are currently focused on for Medical Engineering and Science (IMES). His group applies understanding fundamental mechanisms of photodetection in interdisciplinary skills to medical imaging at the intersection superconducting nanowires, and on applying superconducting of engineering, computation, physics, science, and medicine. nanowires to classical electronic computing. From 2010 to 2016, he served as associate director of the Madrid-MIT M+Visión Consortium. This partnership of leaders Antonio Torralba is a professor in the computer vision in science, medicine, engineering, business, and the public group in the Computer Science and Artificial Intelligence sector was dedicated to catalyzing change in Madrid’s health- Laboratory (CSAIL). His work focuses on novel approaches care innovation ecosystem by accelerating translational for image and video understanding. His goal is to build research and encouraging entrepreneurship. integrated vision systems that recognize objects, reason about contextual relationships between objects and places, and understand people and their actions. With his collaborators, he created the LabelMe annotation tool and a number of other curated databases that are widely used by the computer vision community.

eecs.mit.edu 2017 CONNECTOR faculty 45 LYNCH, OZDAGLAR NAMED EECS ASSOCIATE DEPARTMENT HEADS

Two Department of Electrical Engineering and Computer Science (EECS) faculty members were named associate department heads during the 2016-2017 academic year.

Nancy Lynch, the NEC Professor of Software Science and Engineering, became associate department head in September 2016. She succeeded Silvio Micali, the Ford Professor of Computer Science and Engineering, who had served as associate department head since January 2015.

Lynch is known for her fundamental contributions to the foundations of distributed computing. Her work applies a mathematical approach to explore the inherent limits on computability and complexity in distributed systems.

Her best-known research is the “FLP” impossibility result for distributed consensus in the presence of process failures. Nancy Lynch Asu Ozdaglar Other research includes the I/O automata system modeling frameworks. Lynch’s recent work focuses on wireless network algorithms and biological distributed algorithms.

The longtime head of the Theory of Distributed Systems systems and data processing. She is a co-author of Convex research group in the Computer Science and Artificial Analysis and Optimization. Intelligence Laboratory (CSAIL), Lynch joined MIT in 1981. She received a BS from Brooklyn College in 1968 and a PhD Ozdaglar’s research focuses in large part on integrating from MIT in 1972, both in mathematics. Recently, Lynch served analysis of social and economic interactions into the study as head of CSAIL’s Theory of Computation (TOC) group for of networks. Her work spans many dimensions of this area, several years. including analysis of learning and communication, diffusion and information propagation, influence in social networks, She is also the author of several books and textbooks, and study of cascades and systemic risk in economic and including the graduate textbook Distributed Algorithms, financial systems. She continues to make key game-theory considered a standard reference in the field. Lynch has also contributions, including learning dynamics and computation of co-authored several hundred articles about distributed Nash equilibria. algorithms and impossibility results, and about formal modeling and verification of distributed systems. She is the In October 2014, Ozdaglar became the director of the recipient of numerous awards, an Association for Computing Laboratory for Information and Decision Systems (LIDS) and Machinery (ACM) Fellow, a Fellow of the American Academy the associate director of the Institute for Data, Systems, and of Arts and Sciences, and a member of both the National Society (IDSS). Ozdaglar was also a Technical Program Co- Academy of Science and the National Academy of Engineering. Chair of the 2015 Rising Stars program in EECS.

Asu Ozdaglar, the Joseph F. and Nancy P. Keithley Professor of Ozdaglar has also organized numerous conferences Electrical Engineering, became associate department head in and sessions on game theory, networks, and distributed January 2017. Ozdaglar succeeded David Perreault, professor optimization. She received the prestigious Donald P. Eckman of electrical engineering, who had served in the role since Award from the American Automatic Control Council, and November 2013. she was the inaugural recipient of the Steven and Renee Finn Faculty Research Innovation Fellowship at MIT. Ozdaglar is best known for her contributions in the areas of optimization theory, economic and social networked systems, Editor’s Note: As this issue went to press, long-time EECS and game theory. She has made several key contributions to department head Anantha Chandrakasan was named Dean of the optimization theory, ranging from convex analysis and duality MIT School of Engineering, effective July 1. Ozdaglar will serve as to distributed and incremental algorithms for large-scale interim department head during the search for Chandrakasan’s successor.

46 faculty CONNECTOR 2017 eecs.mit.edu REGINA BARZILAY NAMED DELTA ELECTRONICS PROFESSOR

Regina Barzilay has been appointed the Delta Electronics Professor of Electrical Engineering and Computer Science at MIT. The appointment recognizes Barzilay’s leadership in the area of human language technologies and her outstanding mentorship and educational contributions.

“Professor Barzilay is internationally known in the fields of natural language processing and computational linguistics, and is widely respected as a creative thought leader,” Anantha Chandrakasan, head of the Department of Electrical Engineering and Computer Science (EECS) and the Vannevar Bush Professor of Electrical Engineering and Computer Science wrote in a note announcing the appointment. “In addition to this research, she has made truly outstanding educational contributions.”

Barzilay’s research on natural languages focuses on the development of models of natural language, and uses those models to solve real-world language processing tasks. Her research in computational linguistics deals with multilingual learning, interpreting text for solving control problems, and finding document-level structure within text. Barzilay’s work enables the automated summarization of documents, machine was also program co-chair of the 2015 Rising Stars workshop interpretation of natural language instructions, and the for women in computer science and electrical engineering deciphering of ancient languages. As the world has more and workshop at MIT. more text to be searched and interpreted, applications for this work increase year by year. Barzilay is a recipient of various awards, including the National Science Foundation Career Award, the MIT Technology Jointly with Professor Tommi Jaakkola, Barzilay developed Review Innovators Under 35 Award, a Microsoft Faculty the popular Introduction to Machine Learning course (6.036), Fellowship, and several best paper awards in top natural which enrolled 500 students in spring 2017. Barzilay has language-processing conferences. also recently revised the format of 6.864 (Advanced Natural Language Processing). That class’s content was modified to incorporate applications of deep neural networks to natural language processing, material covered almost exclusively in research papers. In addition, the class was reformatted to emphasize project-driven learning. This format helped multiple students — especially undergraduates — to start their own research in natural language processing. Barzilay was recognized for her educational contributions with the Jamieson Teaching Award in 2016.

Barzilay has also made valuable professional contributions in her field and in the department. She serves as the action editor for the Transactions of the Association for Computational Linguistics. She served as the program co-chair for the Conference on Empirical Methods in Natural Language Processing (EMNLP) in 2011, and is a chair of the 2017 Association of Computational Linguistics Conference. She eecs.mit.edu 2017 CONNECTOR faculty 47 DUANE BONING APPOINTED LEBEL PROFESSOR IN EECS

Duane Boning has been named the Clarence J. LeBel Professor of Electrical Engineering. The chair is named for Clarence Joseph LeBel ‘26, SM ‘27, who co-founded Audio Devices in 1937 and was a pioneer in recording discs, magnetic media for tapes, hearing aids, and stethoscopes.

“Boning’s teaching is recognized as outstanding at both the undergraduate and graduate levels, and he is a leader in the field of manufacturing and design,” noted Anantha Chandrakasan, the Vannevar Bush Professor of Electrical Engineering and Computer Science and head of the Department of Electrical Engineering and Computer Science (EECS). “This is fitting recognition of his outstanding contributions to research, teaching, mentoring, and service.”

Boning’s research focuses on manufacturing and design, MIT Leaders for Global Operations (LGO) program and became with emphasis on statistical modeling, control, and the engineering faculty co-director for LGO in September 2016. variation reduction in semiconductor, MEMS, photonic, and Since 2011, he has served as the director for the MIT/Masdar nanomanufacturing processes. His early work developed Institute Cooperative Program, fostering many joint activities computer integrated manufacturing approaches for flexible between MIT and Masdar Institute, an engineering university in design of IC fabrication processes. He also drove the Abu Dhabi, United Arab Emirates. From 2011 through 2013, he development and adoption of run-by-run, sensor-based, and served as founding faculty lead in the MIT Skoltech Initiative, real-time model-based control methods in the semiconductor working to launch the Skolkovo Institute of Science and industry. He is a leader in the characterization and modeling of Technology (Skoltech) near Moscow, Russia. spatial variation in IC and nanofabrication processes, including plasma etch and chemical-mechanical polishing (CMP), Within MIT, Boning has served on several Institute committees, where test mask design and modeling tools developed in his including as chair of the Committee on Undergraduate group have been commercialized and adopted in industry. Admissions and Financial Aid (CUAFA) in 2007, and he served Boning served as editor in chief for the IEEE Transactions on as chair of the Committee on the Undergraduate Program Semiconductor Manufacturing from 2001 to 2011, and was (CUP) in 2016-2017. named a fellow of the IEEE for contributions to modeling and control in semiconductor manufacturing in 2005.

In addition to creating the graduate-level course Control of Manufacturing Process (6.780J/2.830J), he has lectured in several core EECS subjects, including Signals and Systems (6.003) and Structure and Interpretation of Computer Programs (6.001). His teaching has been recognized with the MIT Ruth and Joel Spira Teaching Award. Boning won the Best Advisor Award from the MIT ACM/IEEE student organization in 2012 and the 2016 Capers and Marion McDonald Award for Excellence in Mentoring and Advising in the School of Engineering.

Boning served as associate department head in EECS from 2004 to 2011. He has previously and presently serves as associate director in the Microsystems Technology Laboratories, where he oversees the information technology and computer-aided design services organization in the laboratories. He is a long-standing and active participant in the

48 faculty CONNECTOR 2017 eecs.mit.edu TOMMI JAAKKOLA NAMED INAUGURAL SIEBEL PROFESSOR

Tommi Jaakkola, a professor of computer science and engineering, has been named as the inaugural holder of the Thomas Siebel Professorship in the Department of Electrical Engineering and Computer Science (EECS) and the Institute for Data, Systems, and Society (IDSS).

The appointment was announced in April 2017 by EECS Department Head Anantha Chandrakasan, Vannevar Bush Professor of EECS, and IDSS Director Munther A. Dahleh, William Coolidge Professor of EECS. “The appointment recognizes Professor Jaakkola’s leadership in the area of machine learning and his outstanding mentorship and educational contributions,” Chandrakasan and Dahleh wrote in a message to EECS faculty. “Professor Jaakkola is internationally well-known in the fields of machine learning and natural language processing, as well as in computational biology. He is widely respected as an original researcher and has made high-impact contributions.”

The new professorship was established through the generous Together with Professor Regina Barzilay, he developed the contribution of veteran software entrepreneur Thomas Siebel, undergraduate machine learning course, which now enrolls Chairman and CEO of C3IoT. Siebel is well-known at MIT more than 500 students per term. He modernized the advanced for having established the Siebel Scholars program, which NLP course, again taught with Barzilay, from the point of view annually provides support for 16 MIT graduate students (five of neural approaches to NLP. In 2015, Jaakkola received the in EECS, five in Biological Engineering, five in the MIT Sloan Jamieson Award for Excellence in Teaching in recognition of his School of Management, and one in Energy Science). educational contributions.

At the core of Jaakkola’s research are inferential and He has also made valuable professional contributions in estimation questions in complex modeling tasks, ranging from his field and within EECS. He has held editorial positions developing the underlying theory and associated algorithms on prestigious journals such as the Journal of Machine to translating such advances into applications. He has been Learning Research and the Journal of Artificial Intelligence a leading contributor to developing distributed probabilistic Research. He has also co-chaired or overseen areas of major inference algorithms from this field’s inception to its current conferences, including the Conference on Neural Information state as a well-established area of research. Processing Systems (NIPS), the Conference on Uncertainty in Artificial Intelligence (UAI), and the Conference on Artificial From the modeling point of view, Jaakkola’s work covers Intelligence and Statistics (AISTATS). He served for many a broad spectrum of areas, from the interface between years on the EECS Faculty Search Committee and has been a generative and discriminative modeling, rethinking modeling member of other committees as well. He has also contributed from the point of view of randomization and combinatorial to the career paths of many students and postdocs that he optimization, to recovery questions associated with continuous has supervised and mentored at MIT. Former students and embedding of objects. In natural language processing (NLP), postdocs from his research group now hold positions in leading his contributions include solving hard combinatorial inference universities such as MIT, CMU, and UC Berkeley. problems such as natural language parsing, developing deep convolutional representations of text, and reframing complex As an affiliate member of IDSS, Jaakkola has been models to reveal interpretable rationales for prediction. instrumental in both the hiring and recruitment of statistics Several of his papers have received best-paper awards at faculty as well as the creation of programs in statistics. He has leading events. served on the IDSS Statistics Faculty Search Committee from the start, and worked with the IDSS Statistics PhD Committee In addition, Jaakkola “has made outstanding educational to develop a proposal for a dual PhD degree. He is also a contributions,” Chandrakasan and Dahleh noted. He participant in the Statistics and Data Science MicroMasters. established and oversaw the growth of the graduate machine learning course, teaching it for many years until Professor Leslie Kaelbling took it over for further development. eecs.mit.edu 2017 CONNECTOR faculty 49 RUSS TEDRAKE APPOINTED TO INAUGURAL TOYOTA PROFESSORSHIP

Russ Tedrake, a faculty member in the Department of Electrical Engineering and Computer Science (EECS), has been named as the inaugural chair holder of the Toyota Professorship.

The appointment was announced in May 2017 by Anantha Chandrakasan, EECS department head and Vannevar Bush Professor of Electrical Engineering and Computer Science, and Ian Waitz, Dean of the School of Engineering. “The appointment recognizes Professor Tedrake’s leadership in the area of robotics and his outstanding mentorship and educational contributions,” Chandrakasan and Waitz wrote in a message to faculty. “Professor Tedrake is internationally well-known in the field of robotics, and is widely respected for his theoretical, algorithmic, and experimental contributions to the field.”

Tedrake’s research focuses on developing optimization- based algorithms for planning, feedback control, and analysis of complex dynamic robots that can walk, run, and fly through unstructured environments. His work leverages the observation that the equations of motion of these robots, constrained by mechanics, have special structure. By finding new connections between convex optimization and the mathematical models of, for example, frictional contact mechanics, he has been able to make seemingly intractable problems in robot feedback control become tractable.

Tedrake’s algorithmic results have led to impressive demonstrations on real hardware. His algorithms enabled the first successful demonstrations of high-speed (post-stall) perching for fixed-wing unmanned aerial vehicles (UAVs); his small airplanes could land on a perch like a bird. More recently, his team has developed bird-sized UAVs that can dart campus,” Chandrakasan and Waitz wrote. “His Underactuated through trees at more than 30 mph, guided by a provably robust Robotics course was one of the first two graduate courses to feedback motion planning engine. He also led MIT’s entry in be put on edX, with a current enrollment exceeding 20,000 the DARPA Robotics Challenge, demonstrating optimization- students, and his course notes and open-source software are based perception, planning, and feedback control for a complex widely known in the robotics community.” Tedrake has also humanoid that had to drive a car, open doors, turn valves, pick been instrumental in updating the core controls and signal up and operate power tools, and walk across rough terrain and processing curriculum, and has been recognized with both the up stairs. Jerome H. Saltzer Award and the Ruth and Joel Spira Award for his undergraduate teaching. Tedrake has been a leader in organizing robotics activities across campus. He started the Robotics@MIT seminar series and the Robotics@MIT Student Conference, and serves as faculty advisor for many of the robotics student groups and projects at MIT.

“Professor Tedrake has made truly outstanding contributions to both graduate and undergraduate education both on and off

50 faculty CONNECTOR 2017 eecs.mit.edu NEW CAREER DEVELOPMENT CHAIRS

Thomas Heldt Stefanie Mueller Max Shulaker W. M. Keck Career Development X-Consortium Career Emmanuel E. Landsman (1958) Professor in Biomedical Development Assistant Career Development Assistant Engineering Professor Professor

Justin Solomon David Sontag Virginia Williams X-Window Consortium Career Hermann L. F. von Helmholtz Steven G. (1968) and Renee Finn Development Assistant Career Development Assistant Career Development Associate Professor Professor Professor

NEW FACULTY

Adam Belay

Belay will join EECS as an assistant professor in July 2017. He received a PhD in computer science from Stanford University, where he was a member of the secure computer systems group and the multiscale architecture and systems team. Previously, he worked on storage virtualization at VMware Inc. and contributed substantial power-management code to the Linux Kernel project. Belay’s research area is operating systems and networking. Much of his work has focused on restructuring computer systems so that developers can more easily reach the full performance potential of hardware. He received a Stanford graduate fellowship, a VMware graduate fellowship, and a Jay Lepreau Best Paper award from the USENIX Symposium on Operating Systems Design and Implementation (OSDI).

eecs.mit.edu 2017 CONNECTOR faculty 51 Stefanie Mueller

Mueller joined EECS as an assistant professor in January 2017. She received a PhD in human-computer interaction (HCI) from the Hasso Plattner Institute in 2016, where she also received a master’s degree in IT-systems engineering. In her research, Mueller develops novel interactive hardware and software systems that advance personal fabrication technologies. Her work has been published at the most selective HCI venues — Association for Computing Machinery (ACM), the Conference for Human Factors in Computing Systems (CHI), and User Interface Software and Technology (UIST) — and received a best-paper award and two best- paper nominations. Mueller is an associate chair of the program committees at ACM, CHI, and UIST, and is a general co-chair for the ACM SIGGRAPH Symposium on Computational Fabrication at MIT in June 2017. She has been an invited speaker at MIT, Stanford, the University of California at Berkeley, Harvard, Carnegie Mellon University, Cornell University, Microsoft Research, Disney Research, Adobe Research, and others. In addition, her work has been covered by New Scientist, the BBC, The Atlantic, and The Guardian. Mueller heads the HCI engineering group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), which works at the intersection of human-computer interaction, computer graphics, computer vision, and robotics. She was included in the Forbes “30 Under 30 in Science” list for 2017, and was named an X-Consortium Career Development Assistant Professor in EECS.

Max Shulaker

Shulaker joined EECS as an assistant professor in July 2016. He received his bachelor’s, master’s, and PhD degrees in electrical engineering at Stanford, where he was a Fannie and John Hertz Fellow and a Stanford Graduate Fellow. Shulaker’s research focuses on the broad area of nanosystems. His Novel Electronic Systems Group aims to understand and optimize multidisciplinary interactions across the entire computing stack — from low-level synthesis of nanomaterials, to fabrication processes and circuit design for emerging nanotechnologies, up to new architectures — to enable the next generation of high performance and energy- efficient computing systems.

David Sontag

Sontag joined EECS in January 2017 as an assistant professor. He is also part of MIT’s Institute for Medical Engineering and Science (IMES) and the Computer Science and Artificial Intelligence Laboratory (CSAIL). Before coming to MIT, he had been an assistant professor in computer science and data science at New York University’s Courant Institute of Mathematical Sciences since 2011. Previously, he was a postdoc at Microsoft Research New England. Sontag’s research interests are in machine learning and artificial intelligence with a recent focus on unsupervised learning, a problem of discovering hidden variables from data, and causal inference, which seeks to estimate the effect of interventions from observational data. At IMES, he will lead a research group that aims to transform health care through the use of machine learning. Sontag received CSAIL’s George M. Sprowls award for his PhD thesis at MIT in 2010, best-paper awards at several conference, and a National Science Foundation CAREER Award in 2014. He received a bachelor’s degree in computer science from UC Berkeley and master’s and PhD degrees in electrical engineering and computer science from MIT. He has been named the Hermann L. F. von Helmholtz Career Development Assistant Professor at IMES.

52 faculty CONNECTOR 2017 eecs.mit.edu Ryan Williams

Williams joined MIT as an associate professor in EECS in January 2017. He received a bachelor’s degree in computer science and mathematics from Cornell, and a PhD in computer science from Carnegie Mellon. Following postdoctoral appointments at the Institute for Advanced Study (Princeton) and IBM Almaden, he was an assistant professor of computer science at Stanford for five years. Williams’ research interests are in the theoretical design and analysis of efficient algorithms and in computational complexity theory, focusing mainly on new connections (and consequences) forged between algorithm design and logical circuit complexity. Along with some best-paper awards, Williams has received a Sloan Research Fellowship, a National Science Foundation CAREER Award, and a Microsoft Research Faculty Fellowship, and he was an invited speaker at the 2014 International Congress of Mathematicians.

Virginia Vassilevska Williams

Williams joined EECS as an associate professor in January 2017. She received a bachelor’s degree in mathematics and engineering and applied science from Caltech and a PhD in computer science from Carnegie Mellon. She was a postdoctoral fellow at the Institute for Advanced Study at (Princeton), UC Berkeley, and Stanford. Prior to joining MIT, she spent more than three years as an assistant professor at Stanford. Her research interests are broadly in theoretical computer science, focusing on the design and analysis of algorithms and fine-grained complexity. Her work on matrix multiplication algorithms was covered by the media and was the most cited paper in algorithms and complexity in the last five years. She was named the Steven G. (1968) and Renee Finn Career Development Associate Professor in EECS and was also awarded a Sloan Research Fellowship for work done at Stanford.

eecs.mit.edu 2017 CONNECTOR faculty 53 INSTITUTE PROFESSOR EMERITA MILDRED DRESSELHAUS DIES AT 86

“Queen of carbon science” and recipient of Presidential Medal of Freedom and National Medal of Science led US scientific community, promoted women in STEM.

By MIT News

Mildred S. Dresselhaus, a celebrated and beloved MIT Mildred S. Dresselhaus Photo: Bryce Vickmark professor whose research helped unlock the mysteries of carbon, the most fundamental of organic elements — earning her the nickname “queen of carbon science” — died at age 86 various aspects of graphite and authored a comprehensive on Feb. 20, 2017, in Cambridge, Mass. book on fullerenes, also known as “buckyballs.” She was particularly well known for her work on nanomaterials and Dresselhaus, a solid-state physicist who was Institute other nanostructural systems based on layered materials, Professor Emerita of Physics and Electrical Engineering and like graphene, and more recently beyond graphene, like Computer Science (EECS), was also nationally known for her transition metal dichalcogenides and phosphorene. Her work work to develop wider opportunities for women in science and on using quantum structures to improve thermoelectric energy engineering. conversion reignited this research field.

“Yesterday, we lost a giant — an exceptionally creative scientist “I like to be challenged,” she was quoted as saying. “I and engineer who was also a delightful human being,” welcome the hard questions and having to come up with good MIT President L. Rafael Reif wrote in an email to the MIT explanations on the spot. That’s an experience I really enjoy.” community. “Among her many ‘firsts,’ in 1968, Millie became the first woman at MIT to attain the rank of full, tenured A strong advocate for women in STEM professor. She was the first solo recipient of a Kavli Prize and the first woman to win the National Medal of Science in As notable as her research accomplishments was Engineering.” Dresselhaus’s longstanding commitment to promoting gender equity in science and engineering, and her dedication to Dresselhaus was also, “to my great good fortune, the first to mentorship and teaching. reveal to me the wonderful spirit of MIT,” Reif added. “In fact, her down-to-earth demeanor was a major reason I decided to In 1971, Dresselhaus and a colleague organized the first join this community. Like dozens of young faculty and hundreds Women’s Forum at MIT as a seminar exploring the roles of of MIT students over the years, I was lucky to count Millie as women in science and engineering. She received a Carnegie my mentor.” Foundation grant in 1973 to support her efforts to encourage women to enter those two traditionally male-dominated fields. A winner of both the Presidential Medal of Freedom (from For a number of years, she led an MIT seminar in engineering President Barack Obama, in 2014) and the National Medal for first-year students; designed to build the confidence of of Science (from President George H.W. Bush, in 1990), female students, it always drew a large audience of both men Dresselhaus was a member of the MIT faculty for 50 years. and women. Beyond campus, she held a variety of posts that placed her at the pinnacle of the nation’s scientific enterprise. Just two weeks before her death, General Electric released a 60-second video featuring Dresselhaus. The video imagined Dresselhaus’s research made fundamental discoveries a world in which female scientists like Dresselhaus were in the electronic structure of semi-metals. She studied viewed as celebrities, a message intended to both celebrate

54 faculty CONNECTOR 2017 eecs.mit.edu her achievements and encourage more women to pursue Aside from her Medal of Freedom — the highest award careers in the “STEM” fields (science, technology, engineering, bestowed by the U.S. government upon American civilians — and mathematics). and her Medal of Science, given to the nation’s top scientists, Dresselhaus’s extensive honors included the IEEE Medal of Dresselhaus co-authored eight books and about 1,700 papers, Honor for “leadership and contributions across many fields of and supervised more than 60 doctoral students. science and engineering”; the Enrico Fermi Award from the U.S. Department of Energy for her leadership in condensed “Millie’s dedication to research was unparalleled, and her matter physics, in energy and science policy, in service to the enthusiasm was infectious,” said Anantha Chandrakasan, scientific community, and in mentoring women in the sciences; the Vannevar Bush Professor of Electrical Engineering and and the prestigious Kavli Prize for pioneering contributions Computer Science and head of MIT’s Department of Electrical to the study of phonons, electron-phonon interactions, and Engineering and Computer Science (EECS). “For the past thermal transport in nanostructures. She was also an elected half-century, students, faculty and researchers at MIT and member of the National Academy of Sciences and the National around the world have been inspired by her caring advice. I was Academy of Engineering. In 2016, she received honorary very fortunate to have had her as a mentor, and as an active degrees from Brandeis University, Oxford University, and North member of the EECS faculty. She made such a huge impact on Carolina State University; the last was her 38th such honor. MIT, and her contributions will long be remembered.” Active on campus Diverted from teaching to physics Always an active and vibrant presence at MIT, Dresselhaus Born on Nov. 11, 1930, in Brooklyn and raised in the Bronx, remained a notable influence on campus until her death. She Mildred Spiewak Dresselhaus attended Hunter College, continued to publish scientific papers on topics such as the receiving her bachelor’s degree in 1951 and then winning a development of 2D sheets of thin electronic materials, and Fulbright Fellowship to study at Cambridge University. played a role in shaping MIT.nano, a new 200,000-square-foot center for nanoscience and nanotechnology scheduled to open While she had planned to become a teacher, Rosalyn Yalow in 2018. — who would go on to win the 1977 Nobel Prize in physiology or medicine — encouraged Dresselhaus to pursue physics In 2015, Dresselhaus delivered the keynote address at instead. She ultimately earned an MA from Radcliffe College “Rising Stars in EECS,” a three-day workshop for female in 1953 and a PhD in 1958 from the University of Chicago, graduate students and postdocs who are considering careers where she studied under Nobel laureate Enrico Fermi. From in academic research. Her remarks, on the importance of 1958 to 1960, Dresselhaus was a National Science Foundation persistence, described her experience studying with Enrico Postdoctoral Fellow at Cornell University. Fermi. Three-quarters of the students in that program, she said, failed to pass rigorous exam requirements. Dresselhaus began her 57-year association with MIT in the Solid State Division of Lincoln Laboratory in 1960. In 1967, “It was what you did that counted,” Dresselhaus told the she joined what was then called the Department of Electrical aspiring scientists, “and that followed me through life.” Engineering as the Abby Rockefeller Mauze Visiting Professor, a chair reserved for appointments of distinguished female Dresselhaus is survived by her husband, Gene, and by scholars. She became a permanent member of the electrical her four children and their families: Marianne and her engineering faculty in 1968, and added an appointment in the husband, Geoffrey, of Palo Alto, California; Carl, of Arlington, Department of Physics in 1983. Massachusetts; Paul and his wife, Maria, of Louisville, Colorado; and Eliot and his wife, Françoise, of France. She is In 1985, Dresselhaus became the first female Institute also survived by her five grandchildren — Elizabeth, Clara, Professor, an honor bestowed by the MIT faculty and Shoshi, Leora, and Simon — and by her many students, whom administration for distinguished accomplishments in she cared for very deeply. scholarship, education, service, and leadership. There are usually no more than 12 active Institute Professors on the Gifts in memory of Mildred Dresselhaus may be made to MIT faculty. MIT.nano, the nanoscience/nanotechnology center scheduled to open in 2018. For more details, visit: Scientific leadership and awards annualfund.mit.edu/dresselhaus

In addition to her teaching and research, Dresselhaus served in numerous scientific leadership roles, including as the director of the Office of Science at the U.S. Department of Energy; as president of the American Physical Society and of the American Association for the Advancement of Science; as chair of the governing board of the American Institute of Physics; as co-chair of the recent Decadal Study of Condensed Matter and Materials Physics; and as treasurer of the National Academy of Sciences.

eecs.mit.edu 2017 CONNECTOR faculty 55 ROBERT FANO, COMPUTING PIONEER, DIES AT 98

Professor emeritus helped launch field of information theory and developed early time- sharing computers.

By Adam Conner-Simons and Rachel Gordon | Computer Science and Artificial Intelligence Laboratory (CSAIL)

Robert “Bob” Fano, a professor emeritus in the Department of Electrical Engineering and Computer Science (EECS) whose Robert Fano work helped usher in the personal computing age, died in Photo: Jason Dorfman | CSAIL Naples, Florida, on July 13, 2016. He was 98.

During his time on the faculty at MIT, Fano conducted research In many respects, Fano was one of the world’s first open- across multiple disciplines, including information theory, source advocates. He frequently described computing as a networks, electrical engineering and radar technologies. His public utility that, like water or electricity, should be accessible work on “time-sharing” — systems that allow multiple people to all. His writings in the 1960s often discussed computing’s to use a computer at the same time — helped pave the way for place in society, and predated today’s debates about the ethical the more widespread use of computers in society. implications of technology.

Much of his early work in information theory has directly “One must consider the security of a system that may hold impacted modern technologies. His research with Claude in its mass memory detailed information on individuals and Shannon, for example, spurred data-compression techniques organizations,” he wrote in a 1966 paper he co-authored with such as Huffman coding that are used in today’s high-definition Corbató. “How will access to the utility be controlled? Who will TVs and computer networks. regulate its use?”

In 1961, Fano and Fernando Corbató, professor emeritus in A native of Italy, Fano studied at the School of Engineering of EECS, developed the Compatible Time-Sharing System (CTSS), Torino before moving to the United States in 1939. He earned one of the earliest time-sharing systems. The success of both his bachelor’s degree (1941) and his doctorate (1947) from CTSS helped convince MIT to launch Project MAC, a pivotal MIT in electrical engineering, and was a member of the MIT early center for computing research for which Fano served faculty from 1947 until 1984. as its founding director. Project MAC has since dramatically expanded to become MIT’s largest interdepartmental During World War II, Fano worked on microwave components at research lab, the Computer Science and Artificial Intelligence the MIT Radiation Laboratory and on radar technologies at the Laboratory (CSAIL). Lincoln Lab. He also served as associate head of EECS from 1971 to 1974. “Bob did pioneering work in computer science at a time when many people viewed the field as a curiosity rather than a Over the years, Fano won many notable awards, including rigorous academic discipline,” CSAIL Director Daniela Rus the IEEE’s Educational Medal for teaching and the Claude said. “None of our work here would have been possible without E. Shannon Award for his work in information theory and his passion, insight, and drive.” microwave filters. He was a member of the National Academy of Sciences and the National Academy of Engineering, and a Fano was the Ford Professor of Engineering in EECS and a fellow of the American Academy of Arts and Sciences and the dedicated teacher who would often labor into the late hours of Institute of Electrical and Electronic Engineers. the morning, working on new lectures. He was also a member of multiple research labs at MIT, including the Laboratory for He is survived by his daughters Paola Nisonger SM ’79, Linda Computer Science, the Research Laboratory for Electronics Ryan SM ’82, and Carol Fano, as well as five grandchildren. (RLE), the MIT Radiation Laboratory, and the MIT Lincoln Laboratory. He helped create MIT’s first official curriculum for computer science, which is now the most popular major at the Institute.

56 faculty CONNECTOR 2017 eecs.mit.edu Education News

Machine Learning for Just About Everyone 58

The Internet of (Play) Things 60

Talk Science to Me: The EECS Communication Lab 63

eecs.mit.edu 2017 CONNECTOR faculty 57 MACHINE LEARNING FOR JUST ABOUT EVERYONE

Expanded offerings for one of MIT’s hottest topics reach a broad cross-section of the student population.

By Eric Smalley | Connector Contributor Photo: Lillie Paquette/School of Engineering

Introduction to Machine Learning (6.036) meets in MIT’s largest lecture hall — and professors still had to whittle down the number of students who enrolled for Spring 2017.

n the first day of Introduction to Machine Learning (6.036) education, finance, health care, marketing, politics, and Oin February 2017, the setting looked more like a sold-out science. movie theater than an MIT classroom. Machine-learning technologies such as neural networks have At least 700 students converged on the Institute’s largest been in use for decades, but have become widespread only lecture hall, filling every seat and overflowing into another in recent years because powerful and affordable computing room. Even after being pared to a more manageable resources and large amounts of data are more available, says crowd of about 550, 6.036 had higher enrollment than any Tommi Jaakkola, the Thomas Siebel Professor in EECS and the other introductory course in the Department of Electrical Institute for Data, Systems, and Society (IDSS). He likens the Engineering and Computer Science (EECS) — even larger than rise of machine learning to the rise of electricity: “It creates Introduction to EECS (6.01). capabilities that weren’t there before.”

The surge in interest in machine-learning courses should come EECS has had a graduate-level intro course, Machine Learning as no surprise: It mirrors machine learning’s transformation (6.867) for at least 16 years, says Jaakkola, who originally from a niche technology to a mainstream area of expertise created that course. It’s been further developed by its current that’s very much in demand. In April 2017, an informal search instructors, Leslie Kaelbling, the Panasonic Professor of of Boston-area jobs on Indeed.com, a popular employment Computer Science and Engineering in EECS, and Devavrat website, turned up 805 positions requiring machine-learning Shah, a professor of EECS. As the field took off, so did interest experience, more than those seeking candidates with skills in in 6.867. The class began to include a broader range of PHP, Perl or robotics. At the same time, Amazon had posted students, including some from outside EECS and others who nearly 2,900 jobs companywide for candidates with machine- were more interested in the technology’s applications than the learning expertise. theory behind it. “It was a very mixed population with different demands, so at some point it became untenable to maintain Machine learning is an algorithmic approach to data processing that,” Jaakkola says. “We thought we should really create an that builds models from samples of data sets to describe the undergraduate entry-level machine-learning course.” data and make predictions accordingly. It’s a core component of technologies such as computer vision, natural language Thus was born 6.036, co-developed and co-taught by Jaakkola processing and robotics. The technology is used in a growing and Regina Barzilay, the Delta Electronics Professor of EECS. number of fields, including automation, autonomous vehicles, To address the needs of graduate students who are more

58 education CONNECTOR 2017 eecs.mit.edu interested in applied machine learning, especially those from outside EECS, the department also created a parallel graduate course, Applied Machine Learning (6.862). Graduate students in 6.862 attend the 6.036 lectures and do the 6.036 assignments, “ The surge in interest in machine- but also undertake a semester-long project supervised by learning courses should come as Stefanie Jegelka, X-Consortium Career Development Assistant Professor of EECS. no surprise: It mirrors machine

The sheer number of students interested in the machine- learning’s transformation from learning courses reflects both the technology’s widespread adoption and the high level of expertise it demands. Successful a niche technology to a mainstream practitioners need to understand how to phrase problems as machine-learning problems, know what methods exist, and area of expertise that’s very much be able to choose the appropriate method for each problem, in demand.” Jegelka says.

The courses are also helping students outside the department with their research in their fields. Students in 6.862 come from throughout MIT, including from the Departments of Aeronautics and Astronautics, Architecture, Brain and Cognitive Sciences, Chemical Engineering, Civil Engineering, Economics, Mathematics, Mechanical Engineering, and Physics. “These students are defining a project that uses machine learning for their research, so they are working with data from their domain,” Jegelka says. “They learn and experience how to formulate the problem, and which methods may work for it, and sometimes also see where inventions from the machine learning side are needed to capture the problem fully.”

Projects by students in 6.862 involve a vast range of data-driven topics. Examples include: The course’s popularity reflects machine learning’s evolution from a niche area of expertise to one that’s in high demand among employers. • Predicting the energy usage of buildings based on building features.

• Making predictions about molecules, including The growing use of machine-learning technologies has thermodynamic properties, and the function of proteins naturally led to an increase in the number of student based on their 3D structures. internships requiring machine-learning skills. The machine- learning courses emphasize hands-on, applied learning — • Addr essing problems related to autonomous driving, such as including 6.867, although that course has a stronger theoretical learning driving maneuvers from simulation and recognizing component than the other two. The hands-on approach not the road from sensor data. only helps students learn the material, but also gives them the skills they need to land and succeed in internships. • Identifying cells and membranes from brain imaging. Students in 6.867 work with a large data set, design and run algorithms, modify the algorithms, process the data, and • Anal yzing health insurance uptake in developing countries. see how the different modifications lead to different types of answers, Shah says. This experience helps students outside • Det ecting “fake news.” the classroom; if they find themselves unsure of which method to use for a particular application, they can start with • Anal yzing transportation policies in Chinese cities. algorithms from the machine-learning class. “One of the strengths of this course is helping students get ready to do Ultimately, machine-learning classes are enjoyable for something real,” Shah says. instructors as well, Jegelka says: “It’s a lot of fun and very interesting to work with students on such a diverse set of Similarly, 6.036/6.862 teaches students how various machine- problems and data.” learning methods do and don’t work in practice and what issues are related to them, Jaakkola says: “They actually have to code up an algorithm and run it, and investigate results on real types of problems.”

eecs.mit.edu 2017 CONNECTOR education 59 THE INTERNET OF Photos: Anne Stuart (PLAY) THINGS

In two popular courses, students learn how to program mobile sensors — and savor the connections they make.

By Alison F. Takemura | EECS

nvisible messages fly through the room. With laptops open Voldman believes the course’s appeal stems in part from its Iand microcontrollers at the ready, students are learning how hands-on approach. Week by week, students learn how to to code programs that encrypt their messages, typed on the piece together the same interconnected components you’d microcontrollers called Teensies, so that only their lab partners find in a Fitbit: microcontrollers, gyroscopes, accelerometers, can read them. magnetometers, Wi-Fi chips, and so on.

“It’s like spy stuff,” says freshman Brandon Kramer on an April “I wish I had had something like this when I was a freshman,” afternoon. Except for one thing: they’re not exactly dishing says Joe Steinmeyer, an EECS lecturer and co-creator of the in state secrets. His lab partner, sophomore Abby Bertics, course. “There’s so much stuff out there now. You can go on the divulges that the main topic of their messages has been food. Web and just buy these really amazing parts, like a GPS unit or Wi-Fi unit — and you can do a lot with them. But I think many Kramer and Bertics are taking the introductory course 6.S08 students coming in don’t know where to begin.” (Interconnected Embedded Systems). Only in its second year, the course is already extremely popular. Last year, 160 This course and a more advanced one (6.S062, Mobile and students pre-registered, and the instructors ran a lottery Sensor Computing), which also started last year, both help to accept 40, said Joel Voldman, professor of Electrical make students more familiar with using and integrating Engineering and Computer Science (EECS). This year 240 wirelessly connected devices — the so-called “Internet students signed-up, but the course could only enroll 180. of Things.” The emphases, however, are different. The introductory 6.S08 focuses on building a device, which entails

60 education CONNECTOR 2017 eecs.mit.edu putting together hardware and controlling it by programming in languages C++ and Python. The advanced 6.S062 allows “ How do you build a network of students to build more sophisticated software that harnesses devices that communicate with each data from wireless sensors, such as mobile phones, for different applications. In both courses, students receive the other? Sensors may need to last opportunity to apply the skills they learn from lectures and lab exercises to a final, open-ended project. Some submissions are for months at a time in a remote delights, and others, significant novel contributions. environment, how can you ensure 6.S08: Embedded fun their batteries don’t run down really fast?” “Before the class, I had no idea how to wire anything,” said Jenny Xu, a sophomore who took the course last year and is —EECS Professor Sam Madden, cofounder of 6.S062. now a lab assistant (LA). She loves developing games in her own free time, so, in her final project, she and a partner put together the hardware and software for their own multi-player Voldman wants the course to empower students for situations trivia game. All players could buzz in on their own consoles, ranging from Undergraduate Research Opportunities Program the augmented Teensies used in the class, and scores would projects to issues that might come up at work. “We’d like them appear on a leaderboard. It was a rewarding challenge to make to have the confidence that, if they approach a UROP or job and a game she could play with friends, Xu says. their employer says, ‘We have this equipment, and we need you to put an embedded system around it to control it or get the Last year, sophomore Kenneth Collins and a partner created a data off it,’ they feel like, ‘Yeah, I can do that,’” he says. device to answer a proverbial college-student question: Where can you find free food? The device interacted with a server “The field is changing so fast,” Steinmeyer adds. “A lot of that would go to your Gmail and look at free-food e-mails,” he future engineering is going to be engineering across multiple says. Now an LA, he wants to go a little further with the project, systems.” It’s not going to be just one clean sandbox language possibly putting it on display in his dormitory, as something of like Python, for example, but Python, Javascript, and HTML, all a community service. mashed together, he says: “We’re really trying to give students experience integrating across multiple environments.” One of the instructors’ favorite projects from last year was a skateboard that could give its rider directions. Through use of At the time of this writing, current students haven’t gotten to GPS, the skateboard’s sides would light up to indicate which the projects yet, but they’re still enthused. “There aren’t many way to turn at intersections. The board, which the instructors classes where you’re just building cool things all the time,” still have, glows beautifully with blue LEDs. Bertics says. “It’s my favorite class this semester.”

Completing a final project is a winning feature of the course 6.S062: The software side for Carissa Gadson, a sophomore and LA. “A lot of freshmen asked me, ‘Should I should take it? Is it worth it?’ I always say Geared toward juniors and seniors, 6.S062 looks at how yes, because [at the end] you have something technical that to use mobile sensors from a higher level than 6.S08: you can explain really well.” Recruiters were surprised that she through software. had worked with databases and servers, along with C++ and Python, she says. “I think that really helped with getting my Software is what allows users to extract data from local and internship last summer.” remote sensors — increasingly ubiquitous technologies. “So much of what’s happening in the world today involves sensing and phones and mobile devices,” says Sam Madden, professor of EECS and course co-founder. “There really are some specialized techniques that people should know if they’re working in those environments.” One technique is the Viterbi algorithm to solve a Hidden Markov model, which can be applied to a seemingly simple problem: how to figure out which road a car travelled along, using only a trace of GPS signal collected from the car’s driver.

“This problem can actually be very challenging,” Madden says. He flips open his laptop and pulls up a video of red dots moving along streets in Boston. Each dot is a GPS signal, most likely coming from a phone. “You squint at it, and you’re like, ‘Oh yeah, these match onto the roads pretty well.’ But then you see there’s weird stuff.” He zooms in and dots are sometimes on sidewalks or in the Charles River. Some areas have too little data to tell whether there’s actually a road there or whether the results are being confounded by a rogue pedestrian. eecs.mit.edu 2017 CONNECTOR education 61 When Madden changes the video’s focus to the Massachusetts Turnpike running beneath Boston’s Back Bay neighborhood, New Computer Science the GPS dots drop out — because GPS doesn’t work indoors or Minor Attracts Students underground. And then in Copley Square, the dots get rowdy as GPS signals reflect off the Hancock Tower. from Across the Institute

Road mapping this kind of real data is one of many problems students can tackle in the class, Madden says. “There’s multi Sixty-six students from 14 MIT departments have hop communication. How do you build a network of devices that declared that they will minor in computer science, communicate with each other? Sensors may need to last for taking advantage of a new offering that debuted this months at a time in a remote environment, how can you ensure past fall. their batteries don’t run down really fast?” Designed to enable students to earn credentials in Tackling these problems gives students a foundation to build computer science while they pursue other majors, final projects of their own design — a satisfying experience, the computer science minor ensures that graduates says Natasha Consul, a senior who took the course in 2016. learn the fundamentals of programming, algorithms, “When you have that freedom and independence, that’s when and discrete mathematics. To complete the minor, you learn the most,” she says. students must take six subjects in Course 6, including four required courses in the fundamentals and two Three students — Geronimo Mirano, now a master’s of electives, at least one of which must be at an advanced engineering (MEng) student, and Eric Lau and Harihar level, typically within either artificial intelligence and/or Subramanyam, who have both since graduated — solved a theoretical computer science. tricky problem for their final project. GPS works well outdoors, but because it doesn’t penetrate walls, the team created a “The six courses in the minor program provide a solution for indoor travel, such as in a mall or a museum. Their thorough-going introduction to computer science,” software used noisy video data (from stationary surveillance says Chris Terman, the undergraduate officer for MIT’s cameras) and inertial data (from an individual’s phone) to help Department of Electrical Engineering and Computer people find their bearings. Madden and course co-founder Hari Science (EECS). Balakrishnan, the Fujitsu Professor of Electrical Engineering and Computer Science, call those results exciting. “We Terman noted that before the minor was developed, encouraged them to publish,” Madden says. the only way to earn computer science credentials at MIT was to major in 6-2 (Electrical Engineering Mirano has been too busy with his master’s work to pursue a and Computer Science), 6-3 (Computer Science and paper at the moment. But the class left a lasting impression. Engineering), 6-7 (Computer Science and Molecular It showed him there were “really cool problems to be found Biology) or 18C (Mathematics with Computer Science). in these technologies,” and that the same issues pop up in a The Minor in Computer Science is open to all variety of systems, he says. For example, Fitbit and Google undergraduates except those in courses 6-1 (Electrical maps both grapple with inertial data to figure out trajectories. Science and Engineering), 6-2, 6-3, 6-7, 7 (Biology), The robots he programs in his research must similarly extract and 18C. useful, low-bandwidth information from noisy, high-bandwidth sensors, he says, adding: “It’s all connected.” Students enrolled in the new minor thus far hail from a wide range of departments at MIT, including Aeronautics and Astronautics, Civil and Environmental Engineering, Mechanical Engineering, Mathematics, Economics, and Management.

As of spring 2017, there were 27 sophomores, 26 juniors, and 12 seniors in the degree program. However, more people may actually be pursuing the minor, because students may wait until their senior year to declare a minor, Terman notes.

Overall, the launch of the new minor has been a success, Terman says: “Use of online advising and progress-monitoring has helped keep the administrative burden low, so the minor program is serving a new cadre of students without adding substantially to the department’s advising and teaching load.”

For more information on the new computer science minor, visit eecs.mit.edu/csminor.

62 education CONNECTOR 2017 eecs.mit.edu TALK SCIENCE TO ME The EECS Communication Lab offers open-source, real-time, peer-to-peer help for students and postdocs.

By Alison F. Takemura | EECS Photo: Gretchen Ertl

n the spring of 2015, graduate students communicated a “The Comm Lab is a great resource,” says Priyanka Raina, Iclear message to the Department of Electrical Engineering a PhD candidate in EECS. She consulted the lab for a wide and Computer Science (EECS): They wanted help range of assignments: a conference paper, a presentation, her communicating. resumé, and a faculty package. “It helped me a great deal,” she says. “All the assignments that I worked on with the lab were Specifically, they wanted to give better pitches for research accepted or saw positive results. I even got an interview with a and startup ideas and make presentations that wowed their top university.” colleagues and senior scientists. They also wanted to impress recruiters, who, mentors said, always saw plenty of candidates The EECS Comm Lab is the latest installment of the with technical skills; it was the applicants with strong Communication Lab program, a School of Engineering communication skills who really stood out from the pack. (SoE) resource, affiliated with the Gordon-MIT Engineering Leadership Program. The Departments of Biological Students were particularly stressed during conferences, when Engineering and Nuclear Science and Engineering also have they realized their talks weren’t what they could be, recalls their own communication labs. The model has expanded Samantha Dale Strasser, a PhD candidate in EECS, who was quickly because it serves students when they need it most, among the graduate students who provided the 2015 feedback. notes Jaime Goldstein, the program’s former director. “Coming from MIT, we really want to be not only at the forefront of science, but also the forefront of communicating that “Early scientists need to get funding, get a job, go to science,” she says. conferences, and meet collaborators,” she says. “We insert ourselves at just that right moment with just the right In response, the department launched two initiatives: the information. And peer coaches know how to ask the right EECS Communication Lab, a peer-coaching resource, and a questions because they’re insiders in the field. It’s a real recipe new lab-supported class, Technical Communication (6.S977). for success.” By all accounts, both initiatives have succeeded, resulting not only in improved posters and pitches, but in a stronger Faculty members agree. In addition to that first Technical department-wide awareness of the power of effective Communication class, the Comm Lab has hosted workshops communication as well. and supported other courses. In January 2017, the Comm Lab provided a training session for graduate students The Comm Lab, as it’s affectionately known, employs graduate presenting at the Microsystems Technology Laboratories’ students and postdoctoral associates from across EECS (MTL) Microsystems Annual Research Conference. “Industry to serve as peer coaches. They’re trained in strengthening members and faculty commented that the quality of pitches their own communication skills, including how to consider showed marked improvement this year,” says Ujwal their audience and purpose, motivate their research, and Radhakrishna, a postdoctoral associate in EECS who organized create a narrative, rather than a litany. Then these skilled the conference. communicators, or communication advisors, are ready to provide advisees with one-to-one help. Advisees might be Research abstracts and presentations in Introduction to anyone in the department, including undergraduates, graduate Numerical Simulation (6.336) have also been notably clearer students, and postdoctoral associates. eecs.mit.edu 2017 CONNECTOR education 63 than in the past. “The abstracts felt a lot better organized, with engaging motivations, detailed concise methods and results descriptions, and thoughtful considerations at the end,” says Luca Daniel, the EECS professor who instructed the Comm “ In technical communication, Lab-supported class. “The presentations were also more accessible to a wider audience. My class has students from 12 you really can’t separate the different departments, so that’s essential.”

Daniel wasn’t the only one enthusiastic about the Comm Lab science or engineering from results in his course. When he asked whether he should again use the resource in his course, his students responded with the communication, so our an emphatic “yes,” he says. Students also suggested adding midterm deadlines, in addition to deadlines for final abstracts advisors are ready to tackle and presentations, to encourage even earlier visits to the Comm Lab. “They love the fact that it is other students helping both at once.” them,” Daniel says. —Diana Chien, Director, Diana Chien, the new director of the SoE-wide Communication SoE Communication Lab Lab program, understands the appeal. “In technical communication, you really can’t separate the science or engineering from the communication, so our advisors are ready to tackle both at once,” she says. When EECS clients visit the Comm Lab to, for instance, work on conference survey showed that of the respondents who had visited the lab, presentations with communication advisors, they’re really all would recommend it to a friend. And while many students connecting with peers — people who are “as ready to parse and postdocs haven’t yet used the lab, more than three details about the design of a machine-learning algorithm quarters of non-users surveyed indicated they were still glad as they are to ask strategic questions about audience and that EECS offers the service. storytelling,” Chien says. “The enthusiastic and sustained interest from students and Chien and the communication advisors also created an online faculty tells us the program’s doing exceptionally well,” resource, the CommKit, to guide students through several says Anantha Chandrakasan, the Vannevar Bush Professor common communication tasks, such as a cover letter or a of Electrical Engineering and Computer Science and EECS National Science Foundation (NSF) application. If an impending department head. “I expect the Comm Lab will become a staple deadline precludes students from meeting an advisor in resource in the department.” person, help is still just a click away. Skills taught in the Comm Lab have a clear professional The Comm Lab’s popularity is mounting. Since September impact, says Chris Foy, a PhD candidate in EECS who took 2016, it has provided more than 250 appointments with 150- the communication course and is now a peer coach. He ranks plus advisees. More than 270 students attended workshops on the Technical Communication class as one of his favorites at posters, pitches, thesis proposals, and the Research Qualifying MIT, in part because it taught him how to focus on building Exam (RQE). Feedback from the Comm Lab’s first annual a rationale or a narrative about his research. “Being able to do this is crucial as a scientist because there are so many problems that are, in theory, worth solving,” he says. “But if you can’t construct a story around why you chose this problem,” he adds pointedly, “then why are you solving it?”

Joel Jean, a PhD candidate in electrical engineering, credits his communication-advisor training with helping him clearly explain his vision for working on thin-film solar cells to help address climate change. That effort paid off: Jean won one of MIT’s most prestigious graduate awards, the Hugh Hampton Young Fellowship. “My return on investment from working with the EECS Comm Lab as an advisor has been extraordinarily high,” he says. “And I expect its value, both for me and for students in the department, to keep growing.”

Editor’s Note: Alison F. Takemura is the administrator for the EECS Communication Lab. To learn more: SoE Communications Lab: mitcommlab.mit.edu EECS Communications Lab: mitcommlab.mit.edu/eecs Trained student advisors coach their peers in the EECS Comm Lab. Photo: Alison F. Takemura

64 education CONNECTOR 2017 eecs.mit.edu Alumni News

Michal Depa: An Innovation ‘Ecosystem’ for Better Health Care 66

Dario Gil: On the Cutting Edge of the Cutting Edge 68

Philip Guo: Making Programming Accessible for All 70

Cal Newport: Dual Careers 72

Martin F. Schlecht: Life Beyond MIT 74

Lisa Su: An Industry Leader Returns to MIT 76

Margaret Guo: Swimming Toward Success 78 AN INNOVATION ‘ECOSYSTEM’ FOR BETTER HEALTH CARE

Jana Care, co-founded by EECS alumnus Michal Depa, focuses on high-quality, low-cost solutions for improving diagnostics in emerging markets.

By Stephanie Schorow | Connector Contributor

any consider the smartphone a tool. Some regard it Man annoyance. For Michal Depa, SM ’11, the founder and CTO of a start-up called Jana Care, the smartphone is a platform for delivering life-saving diagnostic tools to underdeveloped countries at a minimal cost.

Inspired by his medical-technology work in MIT’s Department of Electrical Engineering and Computer Science (EECS), Depa has developed the Aina Device (the name is based on the Sanskrit for “mirror”). The device attaches to a smartphone or a tablet and can measure a person’s glucose level, lipid profile, and other blood parameters from a drop of blood on a test strip. The Aina Device was conceived as a way to monitor diabetes — a crucial issue for countries such as India, which has 61 million diabetics, many of whom lack access to quality medical care.

It can also be used for other blood tests for which analyzers can cost up to thousands of dollars in the United States. The Aina Device, however, only costs about $20 to make. The device is now marketed as part of Jana Care’s “ecosystem” of medical technologies and software aimed at providing emerging markets with high-quality innovations.

“The top end of the health care system in India is on a par with the United States, as measured by health outcomes,” says Depa, who divides his time between Boston and Bangalore. “But that top tier is small; most of the country’s health care is not like that. Devices made in the U.S. can make it to the top of the Indian health care system, but getting them across the whole Michal Depa health care system is difficult, mainly due to cost.”

Depa’s goal for Jana Care is to produce technologies that span the breadth of health care systems, serving more than that top tier. And, he adds: “If you can develop something in an emerging market, then you can sell that

66 alumni CONNECTOR 2017 eecs.mit.edu product in the U.S. This is the thesis some people call ‘reverse innovation.’” Depa has developed Depa has been intrigued with reverse innovation since college. Born in Poland and raised in Montreal, Depa a device that studied electrical engineering and researched telecommunications at McGill University, and came to MIT as attaches to a an undergraduate exchange student on a Killam Fellowship in 2007. He became interested in medical technology while smartphone or earning a master’s degree in electrical engineering and computer science from MIT. “I found it was a good way a tablet and can to use technology to improve people’s lives,” he says. He worked on developing algorithms for analyzing cardiac images measure a person’s captured with MRI machines. As a volunteer with the Computer Science and Artificial Intelligence Laboratory glucose level, lipid (CSAIL) Sana Mobile group, he helped create an oral-cancer screening app for health workers to use in India. profile, and other Depa was intrigued with serving blood parameters patients who lacked access to expensive equipment such as, for instance, the MRI machines. He was also impatient from a drop of blood with the long lag time between coming up with an idea and bringing it to market. “The approach in academia is on a test strip. that you try to solve a problem in a way that no one has done before and publish it,” he says. Researchers thus shy away Rather than completing his PhD, Depa decided to focus on from simpler solutions that are similar building Jana Care. “I wanted whatever I was doing to get out to what others have done. But simplicity there sooner,” he says. was what intrigued Depa. Now a 75-employee, for-profit company, Jana Care is In late 2011, he and Sidhant Jena, a funded by private investments and grants. It has advisors Harvard Business School student, from several highly-regarded institutions, including launched Jana Care (“jana” is the Massachusetts General Hospital, and partnerships with Sanskrit word for “people”) to insulin-maker Biocon and pump manufacturer Medtronic. deliver tools for affordable diabetes With the help of these partnerships, Jana Care has shipped management care. The first product was about 3,000 Aina Devices and directly reached 150 primary- the Aina Device, which has an innovative care clinics. The company has also created the “Habits” app proprietary design but was built with as an educational and coaching tool to help patients control mostly off-the-shelf components diabetes and manage other related health conditions. Plans to perform several blood tests at a are underway to test and market devices that will help lower cost than existing analyzers. patients with other chronic conditions. A smartphone or tablet provides the screen, while Wi-Fi connectivity means Depa may have left MIT before earning his PhD, but he the results can be uploaded and stored. emphasizes that he doesn’t consider himself as a risk-taker. The Aina Device offers health-care He believes that no one with a degree from MIT should hesitate professionals point-of-care tests for to launch or join a startup. “If anything, this will benefit HbA1c, glucose, creatinine, hemoglobin, your career,” he says. “MIT does live up to its reputation” — and the lipid profile (which measures meaning the degree matters in the larger world — so when it cholesterol and triglyceride levels). comes to entrepreneurship, “you should go for it.” eecs.mit.edu 2017 CONNECTOR alumni 67 ON THE CUTTING EDGE OF THE CUTTING EDGE

At IBM, EECS alumnus Dario Gil directs a global research team with an ambitious science agenda.

By Stephanie Schorow | Connector Contributor Photo: IBM

ere’s a thought experiment inspired by an interview with know how to do that already — but when we are physically HDario Gil, SM ’00, PhD ’03, the vice president for science engaged with each other, without screens in front of us.” and solutions of IBM Research: If there is a cutting edge to the cutting edge, Gil walks it Two researchers are spiritedly discussing a computing at IBM Research, where he oversees an expansive science problem when one of them opens his laptop computer to agenda that includes the physical sciences, the mathe- check a formula — and the conversation grinds to a halt. matical sciences, and health care and the life sciences. He The researcher now has access to information, but the en- speaks with energy and passion about advances in ambient, gagement has been disrupted. ubiquitous computing as well as in artificial intelligence and cognitive systems. But what if the laptop simply joins the conversation? What if it verbally explains the information? Or outlines While he directs a global organization of some 1,500 re- an analysis? Or even begins to debate the two researchers searchers across 11 laboratories, Gil also spends a few about the solution? hours a day working with his quantum computing team. “It’s healthy for leaders to continue to be deeply involved in some While most of us now think primarily of computers as particular area that you manage because it anchors you and processors of information, Gil sees them as potential feeds you with energy,” he says. collaborators. This love of hands-on research can be directly linked to Gil’s “Imagine a future in which we are talking to each other and MIT days, when he worked in the nanotechnology laboratory the computer system is also collaborating with us,” he says. of EECS Professor Emeritus Henry “Hank” Smith. There, “To me, it has always been very interesting to see the asym- Gil had his first lab experience: creating knowledge, rather metry of how much we expect of computing when we’re than just learning it. “That was intoxicating,” he recalls. alone and how little we expect of it when we are together.” “My imagination was captured by the nano world — the world we could not see.” Someday, however, users will compute together “not as a network in front of our computers over the Internet — we

68 alumni CONNECTOR 2017 eecs.mit.edu Indeed, Smith remembers Gil as an “energetic, friendly graduate student” who was “noticeably helpful to others While most of us now think and unusually creative in the way he approached problems in the lab.” primarily of computers as

In the lab, Gil and other graduate students developed and processors of information, demonstrated a new system for doing nanolithography, Smith says. That new system employs an array of 1,000 Gil sees them as potential diffractive-opitical microlenses and writes patterns much faster and with greater precision than other forms of nanoli- collaborators. thography. “We patented various elements of the technology and spun off a small company, LumArray, Inc.,” Smith says. That company is still operating in Somerville, Mass., provid- ing special lithography services. Currently, he describes himself as “very, very excited right now about quantum computing.” Last year, IBM Research installed a 5-qubit quantum computer in the cloud. “Now The work is an example of how Gil, as Smith puts it, “takes we have 45,000 users from 140 countries who are learning in a comprehensive view of the role of technology in the about quantum computing,” he says. “I’m really passion- larger world and how technology can both create problems ate about our technical and science community around the and solve them.” world engaging with this topic.”

Among the key factors in the development of Gil’s perspec- Gil’s vision for computing, in fact, seems boundless: Can tive was his international experience as a youth. Born in we build machines that are persuasive? That can convince Spain as the youngest of four brothers, Gil grew up spending us? That we can debate with? And that can help solve the his summers learning languages in Ireland, France and Ita- world’s problems? ly. He spent his senior year of high school at Los Altos High School in California, which he considers a pivotal aspect of his life. After graduating as the valedictorian of Stevens Smith answers the last question this way: “I have met with Institute of Technology in Hoboken, N.J., he came to MIT in Dario on a number of occasions for the sole purpose of 1998 to study for a master’s degree and PhD. exchanging ideas on the great problems facing the world and what role a company like IBM can play in helping to solve them: global warming, failed states, and the refugee “The part that I have always admired about MIT is its can- problem, food supply, the role of the Internet in providing do culture and the quality with which it integrates theory education to the Third World and in combating misinforma- and practice,” Gil says. Most telling to him is the ability of tion and radicalism, and the role of social media for good MIT to produce so many alumni that years and decades and otherwise.” later continue to work in engineering and science, their passion undimmed. Gil and his team are also involved with the intersection between genomic diagnosis and advances in artificial In 2003, he graduated from MIT, joined IBM, and had his intelligence that could drive a new level of personalized first child. His advice: “Try not to combine all that within a medical treatment. IBM recently announced a partnership year.” He now has two girls. with Illumina and Quest Diagnostics in which DNA sequenc- ing can be imputed directly into Watson Genomics to create Unlike many of his fellow alumni, Gil has worked for just specific recommendations, such as a tailored treatment for one company since graduating. When he joined IBM, he con- a specific tumor. Or a person’s DNA would be sequenced to tinued working in nanofabrication. He led the team that built try to match it to a clinic trial to improve outcomes. the world’s first microprocessor with immersion lithography in 2004. He later moved into industry solutions, exploring As someone at the forefront of artificial intelligence, Gil smart grids and energy and then into artificial intelligence remains bemused by the tendency to frame debates about and cognitive solutions. As director of Symbiotic Cognitive new technology as a clash between two extremes: robots Systems, he was responsible for the design and creation take over the world on one hand and computers create uto- of three pioneering laboratories and experiential centers: pia on the other where we can all lie on the beach all day. the Cognitive Environments Laboratory, the IBM Research THINKLab, and the IBM Watson Experience Center. “I understand why people like to frame it that way,” he says. “It’s catchy, right? It provokes a reaction. But I don’t think “Over the last 14 years, I have had a chance at multiple either frame is most illustrative of the path that lies ahead.” careers,” he says. “Sometimes you do that with different He advocates a nuanced perspective that technology will companies. I get to do them inside IBM.” progress not because of the fancy new gadget we might build, but “the choices we make as a society.”

eecs.mit.edu 2017 CONNECTOR alumni 69 MAKING PROGRAMMING ACCESSIBLE FOR ALL

Computer science alum Philip Guo aims to lower the barriers to learning programming and data science. Philip Guo By Eric Smalley | Connector Contributor

f Philip Guo were a superhero, his name might be Guo has dedicated himself to overturning these popular I“The Influencer.” Guo, SB ‘05, MEng ‘06, now teaches and perceptions and making programming accessible to as conducts research at the University of California at San Diego, many people as possible. One recent research paper tackles but his impact has been felt far beyond classrooms and labs. that misconception about programming only involving those He has helped millions of people worldwide learn how to hoodie-clad millennials. Instead, Guo studied adults aged program, eased the fears and frustrations of thousands of 60 to 85 to uncover the cognitive and social challenges they doctoral students, and given thousands of people valuable face in learning how to program. The result was a proposal insights into stereotypes and biases in the computing field. for a set of tools and techniques tailored to the needs of older adults. Guo is an assistant professor in the UCSD Department of Cognitive Science, where he teaches human-computer in- The theme of Guo’s research is developing scalable ways to teraction and conducts research on human factors, distance help people learn computer programming and data science. learning, and computing education. The path that led him The centerpiece of this work is Python Tutor, a tool that there began with a childhood dream of studying computer allows people to write code in a browser and see automat- science at MIT, and wound through an MEng thesis on tools ically generated diagrams that illustrate what their code for programmers, a doctoral thesis at Stanford on tools for does. The tool has its roots in the software Guo developed data scientists, visiting researcher positions at Google, edX for his MEng thesis that analyzes C and C++ code to let pro- and Microsoft, and a postdoctoral position back at MIT’s grammers see whether the code is running as expected. In Computer Science and Artificial Intelligence Laboratory addition to Python, the Python Tutor now works with Java, C, (CSAIL). C++, Ruby, JavaScript, and TypeScript. “The C and C++ part of my visualizer tool actually uses a lot of the same ideas Programming and data science are important for all col- from my MEng thesis,” he says. lege students, including those majoring in liberal arts, journalism, fine arts, and design, Guo says, adding: “That’s Python Tutor, which is free and open-source, is widely used reflected in the job market as well.” However, many people in massive open online courses (MOOCs), traditional college shy away from the field because of its perceived difficulty, as courses and e-textbooks, Guo says. By his estimate, Python well as stereotypes about programmers. “The popular im- Tutor has, so far, been used by more than 3.5 million people age is of young people in hoodies crouched over a computer in more than 180 countries to visualize more than 30 million screen and being antisocial,” he says. lines of code.

70 alumni CONNECTOR 2017 eecs.mit.edu In fact, Python Tutor has been the source of Guo’s biggest well-rounded computer science education. It also taught impact, says Rob Miller, a professor of computer science him the value of working with motivated and energizing who was Guo’s postdoc advisor at MIT. The Web is full of faculty and students. “What MIT really brought to the table tutorial sites and novice programming systems, but Python was providing a very intensive and passionate work envi- Tutor is unique because it offers a window inside the ma- ronment,” Guo says. “That has really long-lasting effects chine, automatically drawing pictures similar to those that because, even years later, I’m able to have this determina- a good instructor would draw on a blackboard, Miller says. tion and focus and work ethic that I and many of my peers Learning the skills of visualization and mental execution are developed during those years at MIT.” critical to understanding how programs behave, he adds. “Every good programming teacher draws these kinds of See Python Tutor at pythontutor.com. Read the PhD Grind Blog pictures. Philip’s is the first work I’ve seen that can create at phdgrind.com and the Silent Technical Privileges them automatically, for hundreds of simultaneous users, for blog at pgbovine.net/tech-privilege.htm. (Editor’s Note: every major language that people are trying to learn,” Miller Philip Guo is unrelated to Margaret Guo, profiled elsewhere says. “That’s a tremendous benefit to the world.” in this publication.)

Beyond his core research and teaching, Guo has served as an informal mentor to thousands of PhD students, in- The theme of Guo’s cluding many in fields far removed from computer science, by way of a virally popular e-book about his own experience earning a doctorate. The PhD Grind is a personal narrative research is developing of that six-year journey, which he wrote shortly after completing his degree. Guo says that, unlike numerous scalable ways to help other works offering “how-to” advice for PhD students, his book allows people to identify with him. “I think it’s a mirror people learn computer neuron thing,” he says. “People build empathy and find a way to commiserate.” programming and data Guo has also pointed a spotlight at biases in the computing field, particularly those that hinder female and minority science. The centerpiece of students. He wrote a blog post, Silent Technical Privilege that detailed the advantage he gained from the stereotype this work is Python Tutor, of Asian males as skilled programmers, and contrasted his experience with those of fellow students who didn’t fit that a tool that allows people stereotype. NPR and Slate picked up the blog post, and he has since contributed to research on barriers confronting female programmers, co-authoring a paper about the chal- to write code in a browser lenges they face when they contribute to online forums. and see automatically Guo’s current research is aimed at bringing the same types of tools he’s developed for learning programming to the generated diagrams that field of data science. Just as his programming visualization tool had its roots in his MEng thesis, this line of research illustrate what their code builds on his PhD thesis, which helped researchers boost the productivity of their data analysis workflows. Guo’s goals are to help people learn to work with multiple programming does. The tool has its languages; develop tutorials to help people learn about data quality, numeracy, statistics, machine learning, and roots in the software Guo experimental design; and determine whether these types of tutorials can help novice data scientists avoid common developed for his MEng experimenter biases, statistical misconceptions, and erro- neous data interpretations. “The impact of this will be even bigger than programming because there are going to be thesis at MIT. many more people who do data analysis and data science than who are computer programmers,” he says.

Whatever challenges Guo tackles in the future, his MIT ex- perience has prepared him with more than just a thorough,

eecs.mit.edu 2017 CONNECTOR alumni 71 books opposes workplace innovation. Rather, Newport casts a suspicious eye on the very tools — e-mail, smartphones, Slack THE DUAL — that are supposed to make us more efficient.

Here’s how he provocatively puts it in his popular Study Hacks CAREERS OF Blog: “As a distributed algorithm theorist … when I encounter a typical knowledge economy office, with its hive mind buzz of constant unstructured conversation, I don’t see a super- CAL NEWPORT connected, fast-moving and agile organization — I instead see a poorly designed distributed system.”

Alumnus balances two different worlds: What gives weight to Newport’s words are his teaching computer science and writing accomplishments before, during, and after his years studying computer science at MIT, and his dual career as a computer business bestsellers. scientist and book author. A casual observer might think that he is a 24/7 multi-tasker who rarely takes a break from the By Stephanie Schorow | Connector Contributor computer screen. Instead, Newport professes to live by the idea he espouses in his most recent book, Deep Work: Rules for Focused Success in a Distracted World (Grand Central alvin “Cal” Newport, SM ’06 and PhD ’09, doesn’t see the Publishing/Hachette Book Group, 2016). He keeps — more Cworld the same way that many of his peers do in today’s or less — normal work hours and avoids distractions such as connected, Googling, and multi-tasking workplaces. Where social media and even e-mail. To spend time with his two- and many see productivity, he sees disorganization. Where others four-year-old boys, he doesn’t work in the morning or evening. see communication, he sees distraction. “To get what I need to get done just during normal work hours Not that Newport, Provost’s Distinguished Associate Professor really does require that I’m very focused,” says Newport, who of Computer Science at Georgetown University, is anti- lives in the Washington, D.C., area. That means that when he technology. Nor that the author of several best-selling business works, he works with deep concentration in intense blocks

72 alumni CONNECTOR 2017 eecs.mit.edu At MIT, Newport Love (Grand Central Publishing/Hachette Book Group, 2012). Each book reflected a stage in Newport’s life. “I think I write the book I need, not the book that I think I need to tell people trained in an about,” he says. He wrote So Good “not because I had some great answers I wanted to share, but because I wanted an environment that excuse to do the research to get an answer for myself.” He balanced book-writing with his research at MIT. From 2004 to 2009, he was a research assistant and teaching assistant required intense in the Theory of Distributed Systems Group at the Computer Science and Artificial Intelligence Lab (CSAIL). From 2009 to 2011, he was a postdoctoral associate in CSAIL’s Networks concentration; he saw and Mobile Systems Group. Around that time, he started a blog he continues today. After graduating from MIT, he became a tangible connection an assistant professor of computer science at Georgetown University in 2011; he was named to the distinguished between the ability associate professorship in February 2017. At MIT, Newport trained in an environment that required intense concentration; he saw a tangible connection between to concentrate and the ability to concentrate and quality of output. That led to development of the ideas that would become Deep Work, a Wall Street Journal business bestseller and an Amazon Best Book of quality of output. 2016 Pick in Business and Leadership. “Deep work,” according to Newport, is “the ability to focus without distraction on a cognitively demanding task. It’s a skill that allows you to quickly master complicated information and produce better results in less time.” of time. “That’s in part why I don’t have any social media,” he says. “I don’t Web-surf. I’m hard to reach. That’s because I only Deep work is done without the checks that most people do have so much time if I’m going to produce the stuff that I need throughout their day: a quick glance at the inbox; a quick to produce. I really need to spend that time locked in.” glance at the phone. “We know from the research and experience that these quick checks actually significantly Newport, a boyish-looking 34-year-old, has been “locked in” reduce your cognitive capacity,” he said. This is also why since his high school days near Princeton, N.J., where he and Newport wants to tell people they are “allowed” to stop using a friend launched Princeton Web Solutions, a dot-com era social media. “I don’t use it. I find it’s too addictive for me,” Web development and sourcing company. He went on to attend he says. “It’s going to take me away from the things I really Dartmouth College; before graduating summa cum laude with care about.” a degree in computer science in 2004, he had already written his first book. If you think you can’t live without clicking on your Twitter feed, Newport offers this insight: “Deep work is a trainable skill. “I arrived at college having read lots of business books. You Most people think about intense concentration like a habit, like need them when you’re running a business,” Newport recalls. flossing their teeth, something they know how to do; they really At that point, he wanted to learn more about succeeding in just need to make some more time to do it. The reality is it’s school, dealing with student loans, and similar issues. “Back much more like a skill, like playing the guitar.” In other words: then, you couldn’t find a real, serious advice book for college If you haven’t been practicing, you won’t be very good at it. students. Everything was written to be fun and approachable,” he recalls. “I wanted a book that said, ‘OK, here’s how you get Deep work also has applications for MIT undergraduates, good grades.’” in Newport’s view. “You need to do less, and do what you do better. That’s actually the formula for both success in your Not finding what he sought, he conducted interviews with academic life and also in terms of your own personal health, national and international scholarship winners and used the satisfaction, and happiness,” he says. material to write How to Win at College: Surprising Secrets for Success from the Country’s Top Students (Three Rivers Press, “When I was in college, for example, I didn’t double-major, 2005). Other books followed, including How to Become a I didn’t triple-major. I didn’t join 15 clubs. I did computer Straight-A Student (Three Rivers Press, 2006), which was based science and I wrote. And those have consistently been my two on interviews with 50 straight-A students. A few years later, things. I try to do those things as well as I can.” he entered the business book market with So Good They Can’t Ignore You: Why Skills Trump Passion in the Quest for Work You Visit the Study Hacks Blog at calnewport.com/blog eecs.mit.edu 2017 CONNECTOR alumni 73 LIFE BEYOND MIT A five-time MIT alumnus reflects on his transition from academia to industry Martin F. Schlecht, former EECS professor, — and what it’s like to leave a tenured EECS professorship to become a at SynQor headquarters high-tech entrepreneur.

By Kathryn O’Neill | Connector Contributor

s CEO of SynQor, Martin F. Schlecht oversees one In the 1990s, most DC-to-DC converters were only about Aof the world’s leading suppliers of power electronic 80 percent efficient; they lost the rest of the energy to heat. products. Yet the MIT alumnus might easily have spent his By solving some of the technical challenges involved in entire career in MIT’s Department of Electrical Engineering building DC-to-DC converters using synchronous rectifiers, and Computer Science (EECS). SynQor was able to produce converters that were 90 percent efficient and therefore didn’t need heat sinks or the special Schlecht earned five degrees (SBEE, SBME, SMEE, EE, and construction techniques that provided thermal connection ScD) from the Institute and then spent 15 years on the EECS from the power circuit components to those heat sinks. As a faculty. What prompted the full professor to leave and start result, the company’s converters were smaller, lighter, and a company? “I wanted to do something new,” Schlecht says. easier to fabricate while also providing a higher level of quality “Having spent all my time in academia — I was 43 years old — and reliability than what was then standard in the industry, I decided I wanted to learn something about business.” Schlecht explains.

Schlecht also saw an opportunity: a market need for more “Synchronous rectification was a known idea in a general efficient DC-to-DC converters to meet the rising demand for sense, but it wasn’t adopted in the industry because it was logic circuits that operated on lower and lower voltages, a key very complex to implement, particularly in isolated component in telecom and datacom equipment, as well as converters,” Schlecht says. “What I was able to see — through elsewhere. my connections at MIT — was that there was a fast change in the need for higher efficiency as the voltages needed to Schlecht envisioned a way to significantly improve the power logic circuitry quickly dropped from the 5-volt efficiency of such converters using synchronous rectification standard to values below 1 volt.” At that time, he adds, he — a process that converts AC to DC in synchrony with changes began to focus on developing power circuit topologies and in the polarity of the power circuit waveforms — in a particular architectures that were best suited to address the complexities manner. (While DC-to-DC converters begin with DC input, of implementing synchronous rectifiers. they use power switches to provide AC waveforms to the isolation transformer. For that reason, the secondary-side “During Marty’s work with me in his doctoral program, our AC waveforms need to be rectified or converted back to DC to research group was working at the cutting edge of high- power such components as logic circuits.) frequency power electronics technology,” recalls John Kassakian, professor of electrical engineering in EECS.

74 alumni CONNECTOR 2017 eecs.mit.edu “It was Marty’s creativity and engineering skill that was manufacturing. “After the bubble burst, we placed a lot largely responsible for our achieving what, at the time, was of emphasis on offering not just technology but high quality, a record power-conversion density. I take pride in his having reliability, and manufacturing responsiveness,” he says. leveraged that work into a very successful, U.S.-based, power “I am very proud of our technology. But in retrospect, I’m supply company.” more proud of what we’ve accomplished with our manufacturing capability.” Schlecht launched SynQor in 1998 to provide his novel DC-DC converter technology, and he has since guided the company’s All the company’s products (more than 1 million converters continual growth and diversification. Today, SynQor supplies per year) are manufactured at SynQor’s headquarters in thousands of products — not only DC-DC converters but Boxborough, Mass., about 30 miles northwest of MIT. That also AC-DC power supplies, inverters, uninterruptible power enables the business to respond nimbly to demand and supplies, and filters — to industries ranging from telecom to to provide a significant measure of quality control. “By aerospace and from health care to the military. manufacturing here instead of letting someone do it halfway around the world, we are able to see issues that cause Fortunately for Schlecht, MIT made it easy for him to take the problems,” Schlecht says. “We are able to make continual first step toward entrepreneurship: he received a two-year improvements, and we have.” leave of absence to start his company. “That was a safety net,” Schlecht says. “The real challenge was when the two years Manufacturing in the United States also gives SynQor a were up. Leaving MIT then was a tough decision.” competitive edge, he says: “It’s a wonderful example of how an American company can compete with an offshore However, the telecom industry was booming in the late ‘90s, manufacturer. It’s not by just trying to reduce costs. It’s by also and SynQor had a technological edge. So at first the risk providing features that make it worthwhile for the customer to seemed quite manageable, Schlecht says: “Everyone thought pay a little extra money.” the sky was the limit.” What advice does Schlecht have for others who would like to The fledgling company was put to the test just about six start a company? months after Schlecht left MIT, when the telecom bubble burst. The industry’s collapse was “some 10 times bigger than the “Be able to recognize a problem and be able to solve a problem. Those are important skills to learn,” he says. “Be flexible and willing to change your mind in light of new facts. Know your “ To younger people looking for a priorities and focus on them.” But most important of all, he way to save the world, I would say adds: “Be competitive. You must be driven to win.”

that sometimes the answer is very For Schlecht, founding a company wasn’t just about the simple: just develop a technology startup phase. It was about growing a sustainable business and making the field of power electronics more efficient. “To that’s more efficient than what’s younger people looking for a way to save the world, I would out there and move that technology say that sometimes the answer is very simple: just develop a technology that’s more efficient than what’s out there and move into the marketplace sooner than it that technology into the marketplace sooner than it would otherwise have gotten there. The energy you save the world by would otherwise have gotten there.” this effort can be substantial,” Schlecht says.

—Martin F. Schlecht, CEO, SynQor Almost 20 years have passed since the SynQor’s launch, and Schlecht’s time at MIT is long behind him. However, he has had better-known dot-com crash” of the early 2000s, according the chance to watch his daughter go through the Institute — to The Economist. “The next five to six years were tough for Lisa Schlecht is a 2010 mechanical engineering graduate who everybody in our industry,” Schlecht recalls. Big companies also received two master’s degrees from MIT, in mechanical struggled, and many startups went out of business. engineering and in technology and policy. (Schlecht’s son, Derek, received a bachelor’s degree in mechanical engineering Schlecht met these early challenges with the same problem- from Syracuse University in 2013 and is pursuing a master’s solving approach he’d grown familiar with at MIT: “I was able degree at North Carolina State University.) At SynQor, Schlecht to bring my MIT education and cultural philosophy to bear to has begun to focus on ensuring that the business will continue analyze the situation, and eventually help us grow.” to thrive well past his own tenure at the helm.

Recognizing that technological advantages don’t last forever Looking back now, Schlecht said he considers it a privilege to — “Your competitors will eventually discover what you’re have had two such interesting careers. “I really enjoyed my doing, and all existing players will have comparable products” time at MIT. I enjoyed the things I learned. I enjoyed all the — Schlecht credits SynQor’s survival in part to its business people I met, whether students, faculty, or staff,” he says. strategy and problem-solving culture. “I’m very glad to have had completely different professional life experiences. It’s been fun on both sides.” These factors led SynQor to what Schlecht views as the company’s key competitive advantage today: lean, responsive eecs.mit.edu 2017 CONNECTOR alumni 75 INDUSTRY LEADER LISA SU RETURNS TO MIT

At 2017 PhD hooding ceremony, the Advanced Micro Devices CEO says MIT “taught me how to think.”

By Peter Dizikes | MIT News

hree-time EECS alumna Lisa Su, now the president and TCEO of Advanced Micro Devices, urged MIT’s new doctoral graduates to “dream big” and “work hard every day to solve the world’s toughest problems” in her commencement address at the Institute’s 2017 Investiture of Doctoral Hoods.

MIT professors, clad in the multihued robes representing the universities from which they received their doctorates (including MIT), draped doctoral hoods over students from 26 departments, programs, and centers at the Institute. EECS awarded 95 doctoral degrees during the most recent academic year, and most of those recipients attended the ceremony.

“I encourage each of you to dream big and believe you can change the world, have the courage to take risks and enthusiastically learn from mistakes, and work hard every Photo: Dominick Reuter day to solve the world’s toughest problems,” said Su, who received an SB in 1990, an SM in 1991, and a PhD in 1994. “I think if you do that, I’m pretty sure you will make everybody very proud, and you will be incredibly lucky However, she wound up thriving in a challenging throughout your career.” academic environment. “MIT is pure, and it’s really hard,” Su said. “MIT taught me how to think and solve really In outlining her own experiences in technology and hard problems.” business, which have taken her from the Institute’s laboratories to the executive suite, Su observed that MIT Recalling the many ways that her technical education has been a central influence on her own life and career. encouraged her to pursue a career in management, Su re- “The MIT PhD degree truly shaped who I am in so many counted, “I thought I could make better business decisions ways, both personally and professionally,” she said. because I understood the technology.”

Su came to the U.S. from Taiwan at age 2 and grew up in Su began her career at Texas Instruments. She spent 13 New York City. As an undergraduate at MIT, she developed a years working at IBM, rising to the level of vice president of deep interest in semiconductors; as a graduate student, she the Semiconductor Research and Development Center. She received a master’s degree in management and a doctorate then worked in multiple executive roles at Freescale Semi- focused on research in silicon-on-insulator technology. Su conductor, Inc. She joined Advanced Micro Devices in 2012 quipped that when she entered MIT’s doctoral program, at as a senior vice president and general manager for global the urging of her parents, she was “too young at the time to business units, and served as chief operating officer before know any better.” becoming the CEO.

76 alumni CONNECTOR 2017 eecs.mit.edu Su was named one of the Top 50 World’s Greatest Leaders by Fortune in 2017, and has been named a Top Semiconductor CEO by Institutional Investor in both 2016 and 2017. She was also cited as one of MIT Technology Review’s JUST FOR POSTDOCS Top 100 Young Innovators in 2002. She serves on the board of directors for Analog Devices, the Global Semiconductor Alliance, and the U.S. Semiconductor Industry Association. EECS is MIT’s largest department — so it should come as no surprise that it’s home to a massive MIT Chancellor and Ford Professor of Engineering postdoc community as well. Cynthia Barnhart SM ’86 PhD ’88, who annually presides over the hooding ceremony, introduced Su. While giving Dozens of postdoctoral associates work in the welcoming remarks, Barnhart said she was “thrilled” to four EECS labs: Computer Science and Artificial have Su addressing the graduates, and offered her own Intelligence Laboratory (CSAIL), the Laboratory congratulations to the newly minted doctoral graduates. for Information and Decision Systems (LIDS), the Microsystems Technology Laboratories (MTL), and “Earning a doctoral degree from MIT is no small feat,” the Research Laboratory of Electronics (RLE). EECS’s Barnhart told the assembled graduates. “You have every Postdoc6 initiative helps unite this widely dispersed reason to be proud, to be relieved, and to be filled with hope community for peer networking and skills training. for what the future holds.” “Postdocs come to MIT in what is perhaps the most stressful period in their careers,” notes Nir Shavit, This marks the third year that MIT’s doctoral hooding professor of electrical engineering and computer ceremony has featured a keynote speaker, who is chosen science and Postdoc6 faculty coordinator. “They have with input from MIT faculty and doctoral students. a relatively short period of time to show that they can engage in novel research, typically different from Academic regalia dates to at least the 15th century, but what they did in their PhDs, and at the same time American universities only adopted formal codes for apply for jobs.” graduation gowns and hoods in 1893. MIT doctoral degree robes have had their current design since 1995. MIT One popular offering is the EECS Leadership features a silver-gray robe with a cardinal red velvet front Workshop for Postdocs, a two-day offsite event panel, as well cardinal red velvet bars on the sleeves. offered several times a year for groups of 16 Additional color markings denote whether graduates postdocs. The workshops, held at MIT’s Endicott have received a Doctor of Philosophy (PhD) or a Doctor of House conference center in Dedham, Mass., offer Science (ScD) degree. presentations and interactive sessions tailored to postdocs interested in both academic and The actual doctoral hoods are part of the doctoral robe nonacademic careers. ensemble. After the remarks by Barnhart and Su, all doctoral graduates had their names announced as Workshop attendees actively participate in sessions they walked across the stage, then individually had the on leadership, collaboration, group dynamics, hoods draped on their ensembles by their department or effective communication, and organizational skills program head. such as setting goals and priorities. Facilitators use improvisational-theater techniques as part of that training, creating a microcosm of what happens in the lab. They also establish follow-up peer groups to provide postdocs with supportive networks that last “ I encourage each of you to dream big and long after each workshop ends. believe you can change the world, have the “Key to these workshops is the ability to take the courage to take risks and enthusiastically learn postdocs out of their busy everyday lives and allow from mistakes, and work hard every day to them an interruption-free environment in which they solve the world’s toughest problems.” can reflect on their needs going forward as future scientists and leaders,” Shavit says. —Lisa Su, CEO, Advanced Micro Devices Postdoc feedback has been overwhelmingly positive. Typical was the comment from one recent attendee, who described the intensive workshop as a “very useful and productive experience,” adding: “The material can be applied immediately.”

eecs.mit.edu 2017 CONNECTOR alumni 77 SWIMMING TOWARD SUCCESS

Margaret Guo, NCAA’s 2016 “Woman of the Year,” describes how she balances her passions for learning, leadership, and competitive athletics.

By Stephanie Schorow | Connector Contributor

he first question someone might ask uponlearning Tabout the accomplishments of Margaret Guo ’16 is England Women’s and Men’s Athletic Conference records in simply: “How?” three events, and Guo qualified individually for the Division III Women’s Swimming and Diving Championships. As in: how did she graduate from MIT with dual degrees in electrical engineering/computer science and biological “I don’t particularly think that my MIT education and engineering while maintaining a perfect grade point average swimming were in direct conflict,” says Guo, who has (GPA)—and, among other activities, heading the MIT been swimming since she was a toddler. “I loved being Society of Women Engineers during her senior year? And, surrounded by people who shared a common set of values especially, how did she manage all that while also becoming and a mutual determination to achieve a a national collegiate swimming champion? (In October team goal.” 2016, thanks to that last achievement, Guo won the NCAA’s “Woman of the Year” award — the first MIT student to do so Indeed, she credits her MIT classmates for helping her in the award’s 26-year history.) become “a better version of me.” They helped wake her up for 6 a.m. practices, toiled with her on problem-set So how did she do it all? The answer is simple, yet questions, and supported her during the highs and the lows. surprising: Passion. “The inherently collaborative nature of the school fits well into its innovative vibe,” she says. “We weren’t competing against each other for the grade; we were working together “I think one of the things MIT has taught me is how to to gain a deeper understanding of the world in order to prioritize things that I am passionate about,” says Guo, make it a better place.” a native of San Diego, who is now studying for a medical degree and a PhD at Stanford University. “For me, that meant spending my weekends as part of the Society of Guo has now taken her passion back to the West Coast to Women Engineers, mentoring young girls, and showing pursue an MD/PhD. “Being a student athlete, I’ve been them the wonders of science.” always interested in human physiology and always wanted to explore the physical and functional properties that make us so uniquely human,” she says. “It can be argued that the It also meant spending 20 hours a week practicing in the human body is a basically the world’s most complex system, MIT pool. But Guo says that time spent swimming forced with intertwining feedback loops, a lot of different inputs, her to be more productive elsewhere. “Over the semesters, and a lot of different parallel processes.” I learned to focus on the things I care about and do those things really well,” she says. Taking the viewpoint that diseases might be considered “system failures,” Guo hopes to work on creating directed Her focus brought her star-athlete status: She earned five and effective therapeutics for systems-based diseases, such All-America honors from the College Swimming Coaches as cancer or autoimmune disease. Ultimately, she says, she Association of America, and an additional six all-conference wants to help people lead healthier, happier lives. accolades. In 2016, Guo and her relay teammates set New

78 alumni CONNECTOR 2017 eecs.mit.edu DONOR RECOGNITION

eecs.mit.edu 2017 CONNECTOR alumni 79 The Department of Electrical Engineering and Computer Science is truly grateful for the contributions of all alumni and friends. Listed below are those who made new gifts or commitments of $100 or more during Fiscal Year 2016 (July 1, 2015-June 30, 2016). Donors for FY 2017 will be listed in the next issue of the connector. *

Robert L. Adams SM ’69 Charles H. Campling SM ’48 Rajni J. Aggarwal ’89, SM ’90, PhD ’96 Katelyn Carroll James D. Ahlgren ’55 Michael P. Cassidy ’85, SM ’86 Roger K. Alexander SM ’91 Valentino E. Castellani SM ’66 Nasro Min Allah David L. Chaiken SM ’90, PhD ’94 Tao D. Alter SM ’92, PhD ’95 Stanley G. Chamberlain SM ’62, EE ’63 Abeer A. Alwan SM ’86, EE ’87, ENG ’87, PhD ’92 Cy Chan SM ’07, PhD ’12 Boon S. Ang SM ’93, CSE ’98, ENG ’98, PhD ’99 Ronald D. Chaney ’85, SM ’86, PhD ’93 Colin M. Angle ’89, SM ’91 Daniel K. Chang SM ’92 Erika N. Angle ’04 Hwa-Ping Chang PhD ’95 Craig A. Armiento EE ’77, SM ’77, PhD ’83 Steven B. Chanin ’89, SM ’91 Michael A. Ashburn SM ’96 Arthur C. Chen ’61, SM ’62, PhD ’66 Ash Ashutosh Brian Chen SM ’96, PhD ’00 Haejin Baek ’86 Harry H. Chen SM ’76 Arthur B. Baggeroer EE ’65, SM ’65, ScD ’68 Kan Chen SM ’51, ScD ’54 Eugene J. Baik ’05, MEng ’06 Shu-Wie F. Chen ’86 Eileen J. Baird SM ’87 Yin F. Chen ’14 Esme O. Baker S EE ’00 Donald Chu ’75 David R. Barbour SM ’61 Nelson C. Chu SM ’90 Richard A. Barnes ’68 Shun-Lien Chuang SM ’80, EE ’81, PhD ’83 Robert V. Baron ’71, EE ’77, SM ’77 Man Ciin Paul D. Bassett EE ’85, SM ’85 Douglas R. Cobb SM ’65 Arthur J. Benjamin SM ’77 Lewis D. Collins SM ’65, ScD ’68 John U. Beusch SM ’62, PhD ’65 Satyan R. Coorg SM ’94, PhD ’98 Manish Bhardwaj SM ’01, PhD ’09 Geoffrey J. Coram PhD ’00 Archit N. Bhise ’13 Fernando J. Corbato PhD ’56 H. E. Blanton SM ’49, EE ’55 Thomas H. Cormen SM ’86, PhD ’93 Lenore C. Blum PhD ’68 Jack D. Cowan SM ’60 Manuel Blum ’59, SM ’61, PhD ’64 Elliot M. Cramer ’55 Kevin L. Boettcher SM ’81, EE ’82, PhD ’86 David R. Cuddy EE ’74, SM ’74 Nelson E. Bolen SM ’60, EE ’62 Susan R. Curtis SM ’82, PhD ’85 Michael T. Bolin ’03, MEng ’05 Barbara M. Cutler ’97, MEng ’99, PhD ’03 Tom P. Broekaert SM ’89, PhD ’92 Jerome Daniels Rodney A. Brooks Bahman Daryanian ’77, SM ’80, SM ’86, PhD ’89 Derek L. Bruening ’98, MEng ’99, PhD ’05 George A. Davidson SM ’56 Randal E. Bryant SM ’77, EE ’78, PhD ’81 Ronald De Vergiles Robert R. Buckley EE ’78, SM ’78, PhD ’81 Jeff A. Dean John F. Buford ’79, SM ’81 Douglas J. Deangelis SM ’06 Charles G. Bures ’69 Carrick J. Detweiler SM ’06, PhD ’10 Geoffrey F. Burns SM ’89, PhD ’92 Alpha Doo S ’77 EE

*This material was compiled from Department and Institute records. To report an error in this list, or to be removed from future listings, please contact [email protected].

80 donor recognition CONNECTOR 2017 eecs.mit.edu David H. Doo ’77 Olga P. Guttag Jessie L. Dotson ’89 Wayne H. Hagman SM ’81 Jonathan B. Downey ’06 Walter C. Hamscher SM ’83, PhD ’88 Jon Doyle SM ’77, PhD ’80 Alain J. Hanover ’70 Paul R. Drouilhet ’54, SM ’55, EE ’57 Ralph R. Harik ’01, MEng ’03 Adam M. Eames ’04, MEng ’05 John G. Harris ’83, SM ’86 Bruce A. Eisenstein ’63 Eman S. Hashem SM ’89 Arthur Evans NON ’54 Wendi B. Heinzelman SM ’97, PhD ’00 Robert R. Everett SM ’43 Jerrold A. Heller SM ’64, PhD ’67 Kenneth W. Exworthy SM ’59 Michael Henriques S ’91 EE Robert M. Fano ’41, ScD ’47 Steven J. Henry ’72, SM ’73 Michael D. Feezor ’63 Herbert L. Hess SM ’82 Yuchen Feng ’13 Charles Robert Hewes SM ’67, PhD ’71 Matthew L. Fichtenbaum ’66, SM ’67, EE ’68 Alejandro P. Heyworth ’95 Steven G. Finn ’68, SM ’69, EE ’70, ScD ’75 John S. Hill SM ’60 James G. Fiorenza PhD ’02 Robert O. Hirsch ’48, ’50, SM ’51 Giovanni Flammia PhD ’98 Michael G. Hluchyj EE ’79, SM ’79, PhD ’82 Mark A. Foltz SM ’98, PhD ’03 Theresa H. Hluchyj S EE ’82 G. David Forney Jr. SM ’63, ScD ’65 Karen W. Ho ’94 Paul J. Fox EE ’73, SM ’73 Sou K. Ho Janet A. Fraser SM ’84 Wai K. Ho Thomas H. Freeman ’76, ’77 Roger A. Holmes SM ’58 Robert W. Freund EE ’74, SM ’74 Jerry L. Holsinger PhD ’65 Anna V. Gallagher ’02 Gim P. Hom ’71, SM ’72, EE ’73, SM ’73 Thomas H. Gauss SM ’73 Liang Hong ’06 Steven P. Geiger SM ’74 Merit Y. Hong ’84, SM ’87, PhD ’91 Michael A. Gennert ’80, SM ’80, ScD ’87 Charles W. Hoover ’47 Gwendolyn L. Gerhardt Heidi Hopper Kent L. Gerhardt Tareq I. Hoque ’88, SM ’88, SM ’92 Michael D. Gerstenberger EE ’85, SM ’85 Mary A. Hou ’91, SM ’92 Jeremy S. Gerstle ’99, MEng ’01 Henry H. Houh ’89, ’90, SM ’91, PhD ’98 Edward C. Giaimo ’74, SM ’75 Lisa Houh S ’89 EE Anastasios N. Gianotas ’78 Kay L. Hsu ’90, SM ’91 Carla M. Gianotas S ’78 EE Caroline B. Huang SM ’85, PhD ’91 Arthur A. Gleckler ’88, SM ’92 Hugh Hudler S ’97 EE Kenneth W. Goff SM ’52, ScD ’54 Caleb W. Hug SM ’06, PhD ’09 Nicholas Gothard SM ’62 David L. Isaman SM ’70, PhD ’79 Edmund P. Gould SM ’62 William P. Jaeger SM ’80 Paul A. Green ’73 Hans P. Jenssen ’65, EE ’68, PhD ’71 Julie E. Greenberg SM ’89, PhD ’94 Cynthia K. Johanson ’01 Randall V. Gressang SM ’66, EE ’67 Susan B. Jones Stephen E. Grodzinsky ’65, SM ’67 Charlene C. Kabcenell ’79 Winthrop A. Gross EE ’73, SM ’73 Dirk A. Kabcenell ’75 Sheldon Gruber ScD ’58 Zam K. Kam John V. Guttag Steven Kamerman ’73

eecs.mit.edu 2017 CONNECTOR donor recognition 81 Edward J. Kapp SM ’59 Nathan A. Liskov ’60 Zahi N. Karam SM ’06, PhD ’11 Frank J. Liu EE ’66 John S. Keen ScD ’94 Kurt A. Locher ’88, SM ’89 Stephen T. Kent SM ’76, EE ’78, ENG ’78, PhD ’81 Gary W. Look SM ’03, PhD ’08 Ramin Khorram ’83, SM ’84 Francis C. Lowell SM ’64, EE ’65 Elliotte J. Kim ’12 Allen W. Luniewski EE ’77, SM ’77, PhD ’80 Richard Y. Kim ’83, SM ’88 William F. Maher SM ’80 Kenneth P. Kimi SM ’81 Charles I. Malme SM ’58, EE ’59 Barbara J. Klanderman PhD ’02 Henrique S. Malvar PhD ’86 Gregory A. Klanderman SM ’95 Alexandros S. Manos SM ’96 David L. Kleinman SM ’63, PhD ’67 Jonathan A. Marcus ’06 Thomas F. Klimek SM ’59 Steven I. Marcus SM ’72, PhD ’75 Wolf Kohn SM ’74, PhD ’78 Barry Margolin ’83 Thomas F. Kollar SM ’07, PD ’11, PhD ’11 Elisabeth A. Marley SM ’96, PhD ’00 Ronald B. Koo ’89, SM ’90 Glendon P. Marston ScD ’71 Alisa Kretzmer S EE ’46 Emin Martinian SM ’00, PhD ’04 Ernest R. Kretzmer SM ’46, ScD ’49 Michael Y. McCanna ’11 Shawn Kuo SM ’04 John L. McKelvie SM ’49 Yu-Ting Kuo SM ’94 Ignacio S. McQuirk SM ’91, ScD ’96 Shang-Chien Kwei ’05 Alan L. McWhorter ScD ’55 Prashant Lal ’99 Scott E. Meninger SM ’99, PhD ’05 Yafim Landa ’11, MEng ’13 Dale E. Miller ’63 Emanuel E. Landsman ’58, SM ’59, ScD ’66 Stephen W. Miller ’63 Andrea S. Lapaugh EE ’77, SM ’77, PhD ’80 Sramana Mitra SM ’95 Christopher T. Lee SM ’62, EE ’66 Jama A. Mohamed PhD ’00 Jay K. Lee SM ’81, EE ’82, PhD ’85 Lajos Molnar ’97, MEng ’98 Lily Lee SM ’95, PD ’02, PhD ’02 Guy E. Mongold SM ’59 Michael Lee SM ’95 Warren A. Montgomery EE ’76, SM ’76, PhD ’79 Yang-Pal Lee ’72 Paul Moroney ’74, EE ’77, SM ’77, PhD ’79 Yoong Keok Lee PhD ’15 Joel Moses PhD ’67 Young S. Lee EE ’69, SM ’69 Marianne Mosher ’76 Alan P. Lehotsky ’73 Jose M. Moura EE ’73, SM ’73, ScD ’75 Frederick J. Leonberger SM ’71, EE ’72, PhD ’75 Sean D. Murphy ’91 Alan Levin ’72 Sadiki P. Mwanyoha ’98, MEng ’98 Alexander H. Levis ’63, SM ’65, ME ’67, ScD ’68 Keith S. Nabors SM ’90, PhD ’93 Donald M. Levy SM ’58 Santhosh Narayan ’15 Frank S. Levy ’63 Robert F. Nease SM ’53, ScD ’57 Kevin A. Lew SM ’95 Phillip T. Nee SM ’94, PhD ’99 Anthony J. Ley SM ’63 John W. Neese SM ’79 Ying Li SM ’89, EE ’93, ENG ’93, PhD ’94 Peter G. Neumann Jae S. Lim ’74, SM ’75, EE ’78, ScD ’78 Carl E. Nielsen SM ’58 Catherine Lin Kenneth W. Nill ’61, SM ’63, PhD ’66 Li-Jen T. Lin Paola F. Nisonger SM ’79 Tzu Mu Lin Robert L. Nisonger SM ’78 Barbara H. Liskov S ’60 EE Robert W. Nutting SM ’85

82 donor recognition CONNECTOR 2017 eecs.mit.edu James J. Olsen ’80, SM ’85, PhD ’93 Clifford A. Rose EE ’67, SM ’67 Randy B. Osborne EE ’86, ENG ’86, SM ’86, PhD ’90 Larry S. Rosenstein ’79, SM ’82 Rajesh K. Pankaj SM ’88, PhD ’92 Murray A. Ruben EE ’64, SM ’64 Albert R. Paradis EE ’81, SM ’81, PhD ’86 Melanie B. Rudoy SM ’06, PhD ’09 Lynne E. Parker PhD ’94 Martha Ruest S ’77 EE Thornton S. Paxton SM ’65 William D. Rummler SM ’60, EE ’61, ScD ’63 Hugh M. Pearce SM ’66, EE ’67 Daniel M. Sable ’80 Wendy Peikes ’76 Freddie Sanchez ’00 Paul L. Penfield ScD ’60 Nils R. Sandell SM ’71, EE ’73, PhD ’74 Sharon E. Perl SM ’88, PhD ’92 Frank M. Sauk ’74, SM ’77 David J. Perreault SM ’91, PhD ’97 John E. Savage ’61, SM ’62, PhD ’65 Mary Linton B. Peters ’92 Christopher J. Schaepe ’85, SM ’87 Stephen L. Peters ’91, SM ’92, PhD ’06 Roger R. Schell PhD ’71 Marvin E. Petersen SM ’57 Joel E. Schindall ’63, SM ’64, PhD ’67 Robert J. Petrokubi SM ’68 Martin F. Schlecht ’77, EE ’80, SM ’80, ScD ’82 Michael S. Phillip S EE ’91 Paul S. Schluter EE ’76, SM ’76, PhD ’81 Cynthia A. Phillips SM ’85, PhD ’90 Jean-Pierre Schott EE ’82, ENG ’82, SM ’82, PhD ’89 Lisa A. Pickelsimer SM ’92 Sarah E. Schott ’83 Marilyn Pierce Brian L. Schulz SM ’84 Elliot N. Pinson SM ’57 Richard J. Schwartz SM ’59, ScD ’62 John C. Pinson SM ’54, ScD ’57 Campbell L. Searle SM ’51 Damian O. Plummer ’02 David A. Segal ’89 Michael O. Polley ’89, SM ’90, PhD ’96 Charles L. Seitz ’65, SM ’67, PhD ’71 George H. Polychronopoulos SM ’88, PhD ’92 Philip E. Serafim SM ’60, ScD ’64 Aditya Prabhakar ’00, MEng ’01 Danny Seth SM ’01 James C. Preisig EE ’88, ENG ’88, SM ’88, PhD ’92 Carol L. Seward ’47 Robert A. Price SM ’53 L Dennis D. Shapiro ’55, SM ’57 Frank Quick ’69, SM ’70 Amnon Shashua PhD ’93 Sanjay K. Rao ’02, MEng ’03 Paul J. Shaver SM ’62, ScD ’65 Richard H. Rearwin SM ’54 Henry R. Shomber SM ’80 John A. Redding SM ’76 Minoo N. Shroff ’63 Clark J. Reese SM ’69, EE ’70 Howard J. Siegel ’71 Howard C. Reeve SM ’83 James H. Simons ’58 Donnie K. Reinhard SM ’68, EE ’71, PhD ’73 Marilyn Simons S ’58 MA Ellen E. Reintjes ’73, MCP ’74 Edward M. Singel EE ’75, SM ’75 John F. Reintjes ’66 Jagadishwar R. Sirigiri SM ’00, PD ’02, PhD ’03 Eric Richert Jay R. Sklar SM ’62, PhD ’64 Evan Richert Emilie I. Slaughter ’87, SM ’88 Joan Richert Frank G. Slaughter ’84 John Richert Sandy Sloan Frederick L. Ricker SM ’77 Donald L. Snyder SM ’63, PhD ’66 Jennifer Ricker S EE ’77 Gary H. Sockut SM ’74 Dominic A. Rizzo ’04 Carlton E. Speck ’63, SM ’65, ScD ’70 Roger A. Roach NON ’67 David A. Spencer SM ’71, EE ’72 Joseph J. Rocchio ’57, SM ’58 Richard H. Spencer EE ’57

eecs.mit.edu 2017 CONNECTOR donor recognition 83 Steven V. Sperry SM ’78 Joseph E. Wall EE ’76, SM ’76, PhD ’78 John M. Spinelli SM ’85, PhD ’89 Alexander C. Wang SM ’97, PhD ’04 Peter W. Staecker ’64, EE ’68 Caroline W. Wang ’86 Kenneth R. Stafford SM ’66 Da Wang SM ’10, PhD ’14 Daniel D. Stancil SM ’78, EE ’79, PhD ’81 David Wang ’00, MEng ’00 David L. Standley SM ’86, PhD ’91 Grace I. Wang SM ’07, PD ’11, PhD ’11 Billy J. Stanton SM ’83 Kang-Lung Wang SM ’66, PhD ’70 Andrew F. Stark ’97, MEng ’98 Lawrence C. Wang ’99, ’00, MEng ’03 Clifford S. Stein SM ’89, PhD ’92 Shen-Wei Wang PhD ’68 Gideon Stein SM ’93, PhD ’98 Susan S. Wang ’83 Russell L. Steinweg ’79 Charles M. Watson SM ’70 Eric H. Stern ’73 Jennifer Welch SM ’84, PhD ’88 Melvin L. Stone ’51 Gary L. Westerlund NON ’77 Christopher E. Strangio EE ’76, SM ’76 Donald F. Western SM ’66 Eric J. Stuckey SM ’98 Harold M. Wilensky ’70 Joan M. Sulecki SM ’83 John A. Wilkens PhD ’77 David L. Sulman SM ’69 Lucile S. Wilkens PhD ’77 John D. Summers SM ’84 Daniel M. Willenson ’04, MEng ’12 John Z. Sun SM ’09, PhD ’13 Timothy A. Wilson ’85, SM ’87, ScD ’94 Katherine Swartz ’72 William J. Wilson SM ’63, EE ’64, PhD ’70 Donald L. Tatzin ’73, MCP ’74, ’75 Raydiance R. Wise SM ’07 Maziar Tavakoli Dastjerdi SM ’01, PhD ’06 John W. Wissinger PhD ’94 Joan D. Teller Harvey M. Wolfson EE ’74, SM ’74 Samuel H. Teller Joseph F. Wrinn ’75 Michael L. Telson ’67, SM ’69, EE ’70, PhD ’73, SM ’74 Jun Wu Ahmed H. Tewfik SM ’84, EE ’85, ScD ’87 William W. Wu SM ’67 Barry L. Thompson SM ’88, PhD ’93 Joseph Wylen SM ’50 James M. Thompson ’77 Katsumi Yamane SM ’71 Richard D. Thornton SM ’54, ScD ’57 Ying-Ching E. Yang SM ’85, EE ’86, ENG ’86, PhD ’89 Edward G. Tiedemann PhD ’87 Roy D. Yates SM ’86, PhD ’90 James M. Tien SM ’67, EE ’70, PhD ’72 Vera S. Yaul David A. Torrey SM ’85, EE ’86, PhD ’88 Wayne Y. Yaul Sara Torrey S EE ’88 Anthony Yen SM ’87, EE ’88, ENG ’88, PhD ’92, MBA ’06 Hai V. Tran SM ’85 Robert D. Yingling SM ’68 Charles D. Trawick SM ’80 Robert A. Young PhD ’68 Oleh J. Tretiak SM ’60, ScD ’63 Ryan E. Young ’08 Olivia Tsai ’03 Hai-Feng Yun Frederica C. Turner ’95 Weijie Yun John C. Ufford SM ’75 H. R. Zapp ’63, SM ’65 Filip J. Van Aelten SM ’89, PhD ’92 Ronald E. Zelazo ’66, SM ’67, EE ’69, PhD ’71 Thomas H. Van Vleck ’65 Francis H. Zenie ’56 Juan D. Velasquez SM ’96, PhD ’07 Dale A. Zeskind EE ’76, SM ’76 Matthew D. Verminski SM ’98 Limin Zhang Olga Y. Veselova SM ’03 Yan Zhang Holly A. Waisanen PhD ’07

84 donor recognition CONNECTOR 2017 eecs.mit.edu EECS VISITING COMMITTEE

Front row, left to right: Asu Ozdaglar, Charlene C. Kabcenell, Raymond Stata, Andrew J. Viterbi, Anantha Chandrakasan, Diane B. Greene, Lisa T. Su, Jeannette M. Wing, Nancy Lynch | Back row, left to right: Ash Ashutosh, James A. Goldstein, Katherine Yelick, Giovanni De Micheli, John A. Thain, Vanu G. Bose, Raymie Stata, Eran Broshy, Colin M. Angle, Susie J. Wee

In April 2017, the MIT EECS Visiting Committee made its biennial visit to the department. The Committee operates as an advisory group to the MIT Corporation and the senior administration, offering appraisal, advice, and insights about the department. Chaired by John A. Thain, the committee is made up of leaders in industry and academia, many of whom are MIT alumni. Members heard presentations by School of Engineering and EECS leaders as well as EECS faculty, lab directors, and postdocs, and met with groups of faculty and students. They also toured the Department Teaching Laboratories and the Engineering Design Studio, learning about work in progress, and attended a reception with poster presentations by select SuperUROP students.

SuperUROP presentation during reception Demo during Engineering Design Studio tour

Photos: Mary Ellen Sinkus / Anne Stuart MIT EECS CONNECTOR 2017 PAID Nashua NH Permit #375 Permit U.S. Postage Postage U.S. Non-Profit Org. Non-Profit detector arrays. detector

Ignacio Estay Forno, a junior in EE, is researching a method a researching is EE, in junior a Forno, Estay Ignacio photon single with nanoscale interface to eecs.mit.edu eecs.mit.edu EECS at connected to Stay Technology Massachusetts of Institute Room 38-401 77 Massachusetts Avenue, 02139-4307 MA Cambridge,