Volume 3 Summer 2012
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Department of Biology, Report to the President 2016-2017
Department of Biology Academic year 2016–2017 was exciting and productive for the Department of Biology. The department is considered one of the best biological science departments in the world. Our superb faculty members are leaders in biological research and education. Some of the news regarding our faculty, research, and educational programs is highlighted below. Faculty Count and Departures During AY2017, the Department of Biology had 56 faculty members: 44 full professors, eight associate professors, and four assistant professors. Research homes are distributed among Building 68, the Broad Institute, the Koch Institute for Integrative Cancer Research, the Picower Institute for Learning and Memory, and the Whitehead Institute for Biomedical Research. In addition to 56 primary faculty members, there were six faculty members with secondary appointments in Biology. These joint faculty members provide important connections to other departments, including Brain and Cognitive Sciences, Chemistry, Biological Engineering, and Civil and Environmental Engineering. We are saddened by the loss of Professor Susan Lindquist, who passed away in October 2016. Hidde Ploegh (Whitehead Institute) moved to Children’s Hospital in January 2017. Professor William (Chip) Quinn (Biology/Brain and Cognitive Sciences) retired in July 2016. Faculty Awards Department of Biology faculty members are widely recognized for their contributions to the field. Among our core faculty are three Nobel Laureates, 30 members of the National Academy of Sciences, 28 members of the American Academy of Arts and Sciences, 14 fellows of the American Association for the Advancement of Science, four recipients of the National Science Foundation National Medal of Science, and 15 Howard Hughes Medical Institute (HHMI) investigators. -
2008-Annual-Report.Pdf
whitehead institute 2008 AnnuAl RepoRt. a year in the life of a scientific community empowered to explore biology’s most fundamental questions for the betterment of human health. whitehead institute 2008 annual report a Preserving the mission, contents facing the future 1 preserving the mission, it’s customary in this space to recount and reflect facing the future on the accomplishments of the year gone by. i’ll certainly do so here—proudly—but in many 5 scientific achievement important ways, 2008 was about positioning the institute for years to come. 15 principal investigators many colleges, universities, and independent 30 whitehead fellows research institutions found themselves in dire fiscal positions at the close of 2008 and entered 34 community evolution 2009 in operational crisis reflective of the global economic environment. hiring freezes and large- 40 honor roll of donors scale workforce reductions have become the norm. although whitehead institute is certainly not 46 financial summary insulated from the impact of the downturn, i am 48 leadership pleased and somewhat humbled to report that the institute remains financially strong and no less 49 sited for science committed to scientific excellence. david page, director over the past two years, we have been engaged in a focused effort to increase efficiency and editor & direCtor reduce our administrative costs, with the explicit goal of ensuring that as much of the institute’s matt fearer revenue as possible directly supports Whitehead research. Our approach, which has resulted in assoCiate editor nicole giese a 10-percent reduction in operational expense, has been carefully considered. every decision offiCe of CommuniCation and PubliC affairs has been evaluated not just for its potential effects on our scientific mission, but also for 617.258.5183 www.whitehead.mit.edu possible consequences to the whitehead community and its unique culture. -
ANNUAL REPORT 2019 1 Contents Director’S Letter 1
Whitehead Institute ANNUAL REPORT 2019 1 Contents Director’s Letter 1 Chair’s Letter 3 Members & Fellows 4–5 Science 6 Community 44 Philanthropy 56 2 The Changing Face of Discovery For 37 years, Whitehead Institute has demonstrated an ability to drive scientific discovery and to chart paths into new frontiers of knowledge. Its continuing achievements are due, in substan- tial part, to the unique capacities and dedication of Members who joined the Institute in the 1980s and ‘90s — from Founding Members Gerald Fink, Harvey Lodish, Rudolf Jaenisch, and Robert Weinberg to those who followed, including David Bartel, David Sabatini, Hazel Sive, Terry Orr-Weaver, Richard Young, and me. Those long-serving Members continue to do pioneering science and to be committed teachers and mentors. Yet we have begun an inevitable genera- tional transition: In the last two years, Gerry and Terry have closed their labs, and Harvey will do so this coming year. The exigencies of time mean that, increasingly, Whitehead Institute’s ability to maintain its vigorous scientific leadership depends on our next generation of researchers. As I move toward the conclusion of my term as director, I am particularly proud of the seven current Members and the 14 Whitehead Institute Fellows we recruited during the last 16 years. The newest of those stellar researchers joined us in 2019: Whitehead Institute Member Pulin Li and Whitehead Fellow Kipp Weiskopf. Pulin studies how circuits of interacting genes in individu- al cells enable multicellular functions, such as self-organizing into complex tissues, and her research brilliantly combines approaches from synthetic biology, developmental and stem cell biology, biophysics, and bioengineering to study these multicellular behaviors. -
Optimization of Deep Architectures for EEG Signal Classification
sensors Article Optimization of Deep Architectures for EEG Signal Classification: An AutoML Approach Using Evolutionary Algorithms Diego Aquino-Brítez 1, Andrés Ortiz 2,* , Julio Ortega 1, Javier León 1, Marco Formoso 2 , John Q. Gan 3 and Juan José Escobar 1 1 Department of Computer Architecture and Technology, University of Granada, 18014 Granada, Spain; [email protected] (D.A.-B.); [email protected] (J.O.); [email protected] (J.L.); [email protected] (J.J.E.) 2 Department of Communications Engineering, University of Málaga, 29071 Málaga, Spain; [email protected] 3 School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK; [email protected] * Correspondence: [email protected] Abstract: Electroencephalography (EEG) signal classification is a challenging task due to the low signal-to-noise ratio and the usual presence of artifacts from different sources. Different classification techniques, which are usually based on a predefined set of features extracted from the EEG band power distribution profile, have been previously proposed. However, the classification of EEG still remains a challenge, depending on the experimental conditions and the responses to be captured. In this context, the use of deep neural networks offers new opportunities to improve the classification performance without the use of a predefined set of features. Nevertheless, Deep Learning architec- Citation: Aquino-Brítez, D.; Ortiz, tures include a vast number of hyperparameters on which the performance of the model relies. In this A.; Ortega, J.; León, J.; Formoso, M.; paper, we propose a method for optimizing Deep Learning models, not only the hyperparameters, Gan, J.Q.; Escobar, J.J. -
The Barbara Johnson Reader a John Hope Franklin Center Book the Barbara Johnson Reader the Surprise of Otherness
The Barbara Johnson Reader A John Hope Franklin Center Book The Barbara Johnson Reader The Surprise of Otherness Barbara Johnson edited by melissa feuerstein bill johnson gonzález lili porten keja valens With an Introduction by judith butler and an Afterword by shoshana felman Duke University Press Durham and London 2014 © 2014 Duke University Press Afterword © 2014 Shoshana Felman All rights reserved Printed in the United States of America on acid- free paper ∞ Designed by April Leidig Typeset in Minion Pro by Westchester Publishing Services Library of Congress Cataloging-in-Publication Data The Barbara Johnson reader : the surprise of otherness / edited by Melissa Feuerstein, Bill Johnson Gonzalez, Lili Porten, and Keja Valens, with an introduction by Judith Butler and an afterword by Shoshana Felman. pages cm “A John Hope Franklin Center Book.” Includes bibliographical references and index. isbn 978-0-8223-5419-2 (pbk : alk. paper) isbn 978-0-8223-5403-1 (cloth : alk. paper) 1. Johnson, Barbara, 1947–2009. 2. Feminist literary criticism. I. Feuerstein, Melissa. II. Johnson Gonzalez, Bill, 1970– iii. Porten, Lili. IV. Valens, Keja, 1972– pn98.w64b37 2014 801.'95092—dc23 2013045003 Contents Ac know ledg ments vii Editors’ Preface xi Personhood and Other Objects: The Figural Dispute with Philosophy by Judith Butler xvii Barbara Johnson by Barbara Johnson xxvii part i | Reading Theory as Literature, Literature as Theory 1 The Critical Diff erence: BartheS/BalZac 3 2 Translator’s Introduction to Dissemination (abridged) 14 3 Poetry and Syntax: -
A Neuroevolution Approach to Imitating Human-Like Play in Ms
A Neuroevolution Approach to Imitating Human-Like Play in Ms. Pac-Man Video Game Maximiliano Miranda, Antonio A. S´anchez-Ruiz, and Federico Peinado Departamento de Ingenier´ıadel Software e Inteligencia Artificial Universidad Complutense de Madrid c/ Profesor Jos´eGarc´ıaSantesmases 9, 28040 Madrid (Spain) [email protected] - [email protected] - [email protected] http://www.narratech.com Abstract. Simulating human behaviour when playing computer games has been recently proposed as a challenge for researchers on Artificial Intelligence. As part of our exploration of approaches that perform well both in terms of the instrumental similarity measure and the phenomeno- logical evaluation by human spectators, we are developing virtual players using Neuroevolution. This is a form of Machine Learning that employs Evolutionary Algorithms to train Artificial Neural Networks by consider- ing the weights of these networks as chromosomes for the application of genetic algorithms. Results strongly depend on the fitness function that is used, which tries to characterise the human-likeness of a machine- controlled player. Designing this function is complex and it must be implemented for specific games. In this work we use the classic game Ms. Pac-Man as an scenario for comparing two different methodologies. The first one uses raw data extracted directly from human traces, i.e. the set of movements executed by a real player and their corresponding time stamps. The second methodology adds more elaborated game-level parameters as the final score, the average distance to the closest ghost, and the number of changes in the player's route. We assess the impor- tance of these features for imitating human-like play, aiming to obtain findings that would be useful for many other games. -
Neuro-Crítica: Un Aporte Al Estudio De La Etiología, Fenomenología Y Ética Del Uso Y Abuso Del Prefijo Neuro1
JAHR ǀ Vol. 4 ǀ No. 7 ǀ 2013 Professional article Amir Muzur, Iva Rincic Neuro-crítica: un aporte al estudio de la etiología, fenomenología y ética del uso y abuso del prefijo neuro1 ABSTRACT The last few decades, beside being proclaimed "the decades of the brain" or "the decades of the mind," have witnessed a fascinating explosion of new disciplines and pseudo-disciplines characterized by the prefix neuro-. To the "old" specializations of neurosurgery, neurophysiology, neuropharmacology, neurobiology, etc., some new ones have to be added, which might sound somehow awkward, like neurophilosophy, neuroethics, neuropolitics, neurotheology, neuroanthropology, neuroeconomy, and other. Placing that phenomenon of "neuroization" of all fields of human thought and practice into a context of mostly unjustified and certainly too high – almost millenarianistic – expectations of the science of the brain and mind at the end of the 20th century, the present paper tries to analyze when the use of the prefix neuro- is adequate and when it is dubious. Key words: brain, neuroscience, word coinage RESUMEN Las últimas décadas, además de haber sido declaradas "las décadas del cerebro" o "las décadas de la mente", han sido testigos de una fascinante explosión de nuevas disciplinas y pseudo-disciplinas caracterizadas por el prefijo neuro-. A las "antiguas" especializaciones de la neurocirugía, la neurofisiología, la neurofarmacología, la neurobiología, etc., deben agregarse otras nuevas que pueden sonar algo extrañas, como la neurofilosofía, la neuroética, la neuropolítica, la neuroteología, la neuroantropología, la neuroeconomía, entre otras. El presente trabajo coloca ese fenómeno de "neuroización" de todos los campos del pensamiento y la práctica humana en un contexto de expectativas en general injustificadas y sin duda altísimas (y casi milenarias) en la ciencia del cerebro y la mente a fines del siglo XX; e intenta analizar cuándo el uso del prefijo neuro- es adecuado y cuándo es cuestionable. -
Whitehead Institute Hosts Campbio for Middle School Students
Whitehead Institute Hosts CampBio for LINKS About Whitehead Pulse Middle School Students Contact COMMUNITY NOV E MB E R 8 , 2 0 1 3 B Y DUS TIN GRINNE L L Subscribe Upcoming events Whitehead home In August, Whitehead Institute joined with Science from Scientists to host the first CampBio, a weeklong science program bringing local middle school students to CATEG O RIES Whitehead Institute to learn firsthand how researchers answer biology’s most challenging questions. Community Events Honors and Awards Twentysix 7th and 8th graders attended the program, In the news participating in handson activities, laboratory Multimedia demonstrations and discussions with scientists. “We Research were one of the first research institutions in the area to invite high school students into our labs,” says Amy Tremblay, the Public Programs Officer in charge of SEARCH education and community outreach at Whitehead Institute. “We wanted to offer outreach programs to middle school students as well.” It’s a niche that needs to be met, Tremblay says, given the nation’s increasing commitment to STEM (for Science, Technology, Engineering, and Mathematics) education. Such is the credo of Science from Scientists, the leading inclass science/STEM enrichment program in Massachusetts, and codesigner of CampBio. This spring, Tremblay and her team worked with the Bostonbased nonprofit group to bring the summer program to life. “We’re on the cutting edge of biomedical science,” says Tremblay, “so what better place to introduce kids to research?” She says the students were surprisingly unfiltered during the week’s activities, unpressured by their peers and unafraid to ask questions about complex subjects. -
Evolving Neural Networks Using Behavioural Genetic Principles
Evolving Neural Networks Using Behavioural Genetic Principles Maitrei Kohli A dissertation submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy Department of Computer Science & Information Systems Birkbeck, University of London United Kingdom March 2017 0 Declaration This thesis is the result of my own work, except where explicitly acknowledged in the text. Maitrei Kohli …………………. 1 ABSTRACT Neuroevolution is a nature-inspired approach for creating artificial intelligence. Its main objective is to evolve artificial neural networks (ANNs) that are capable of exhibiting intelligent behaviours. It is a widely researched field with numerous successful methods and applications. However, despite its success, there are still open research questions and notable limitations. These include the challenge of scaling neuroevolution to evolve cognitive behaviours, evolving ANNs capable of adapting online and learning from previously acquired knowledge, as well as understanding and synthesising the evolutionary pressures that lead to high-level intelligence. This thesis presents a new perspective on the evolution of ANNs that exhibit intelligent behaviours. The novel neuroevolutionary approach presented in this thesis is based on the principles of behavioural genetics (BG). It evolves ANNs’ ‘general ability to learn’, combining evolution and ontogenetic adaptation within a single framework. The ‘general ability to learn’ was modelled by the interaction of artificial genes, encoding the intrinsic properties of the ANNs, and the environment, captured by a combination of filtered training datasets and stochastic initialisation weights of the ANNs. Genes shape and constrain learning whereas the environment provides the learning bias; together, they provide the ability of the ANN to acquire a particular task. -
Evolving Autonomous Agent Controllers As Analytical Mathematical Models
Evolving Autonomous Agent Controllers as Analytical Mathematical Models Paul Grouchy1 and Gabriele M.T. D’Eleuterio1 1University of Toronto Institute for Aerospace Studies, Toronto, Ontario, Canada M3H 5T6 [email protected] Downloaded from http://direct.mit.edu/isal/proceedings-pdf/alife2014/26/681/1901537/978-0-262-32621-6-ch108.pdf by guest on 27 September 2021 Abstract a significant amount of time and computational resources. Furthermore, any such design decisions introduce additional A novel Artificial Life paradigm is proposed where experimenter bias into the simulation. Finally, complex be- autonomous agents are controlled via genetically- haviors require complex representations, adding to the al- encoded Evolvable Mathematical Models (EMMs). Agent/environment inputs are mapped to agent outputs ready high computational costs of ALife algorithms while via equation trees which are evolved using Genetic Pro- further obfuscating the inner workings of the evolved agents. gramming. Equations use only the four basic mathematical We propose Evolvable Mathematical Models (EMMs), a operators: addition, subtraction, multiplication and division. novel paradigm whereby autonomous agents are evolved via Experiments on the discrete Double-T Maze with Homing GP as analytical mathematical models of behavior. Agent problem are performed; the source code has been made available. Results demonstrate that autonomous controllers inputs are mapped to outputs via a system of genetically with learning capabilities can be evolved as analytical math- encoded equations. Only the four basic mathematical op- ematical models of behavior, and that neuroplasticity and erations (addition, subtraction, multiplication and division) neuromodulation can emerge within this paradigm without are required, as they can be used to approximate any ana- having these special functionalities specified a priori. -
Mapeig D'innovació Massachusetts
MAPEIG D’INNOVACIÓ MASSACHUSETTS SECTOR BIO-IT / DIGITAL HEALTH 9 de febrer de 2016 CATALUNYA I MASSACHUSETTS CATALUNYA MASSACHUSETTS Sup. (km²) 32,107 27,360 Habitants 7,504,008 6,349,097 PIB (milions €) 199,786 427,365 PIB per càpita (€) 26,624 67,311 Atur 17.7% 4.7% R&D sobre PIB 1.5% 5.67% Universitats 12 122 MASSACHUSETTS INNOVADOR MASSACHUSETTS INNOVADOR KEY INDUSTRIES Financial Services Technology Medicine and Life Sciences Manufacturing Fishing Tourism Big Data Digital Health LIFE SCIENCES UNIVERSITATS El sistema d’ensenyament superior de Massachusetts és dual; és a dir, format per una xarxa de centres públics i una de centres privats. La majoria de les 122 institucions d’educació superior que acull l’estat, i també les més destacades en termes d’excel·lència acadèmica i investigadora, pertanyen a l’àmbit privat, encara que la potència del sistema públic també és remarcable. llistar principals amb algun indicador RECERCA? UNIVERSITATS HARVARD Any fundació: 1636 Faculty members : 2,400 Students: 21,000 Alumni: 323,000 living alumni, Budget: $4,500 milliom MIT Any fundació: 1861 Professors (all ranks): 1,021 Other teaching staff: 809 Students: 11,319 Applicants: 18,356 Admits: 1,447 Percentage admitted: 7.9% Patents granted: 275 Budget: $2,920 million MIT Biology/bioengineering • Bioinstrumentation Engineering Analysis and • Emergent Behaviors of Integrated Cellular Systems Microscopy (BEAM) • Harvard-MIT Division of Health Sciences and • BioInstrumentation Laboratory Technology (HST) • Biological Engineering • Human Genomics Laboratory -
About Whitehead Institute for Biomedical Research Selected
About Whitehead Institute for Biomedical Research Selected Achievements in FOUNDING VISION Biomedical Science Whitehead Institute is a nonprofit, independent biomedical research institute with pioneering programs in cancer research, developmental biology, genetics, and Isolated the first tumor suppressor genomics. It was founded in 1982 through the generosity of Edwin C. "Jack" Whitehead, gene, the retinoblastoma gene, and a businessman and philanthropist who sought to create a new type of research created the first genetically defined institution, one that would exist outside the boundaries of a traditional academic human cancer cells. (Weinberg) institution, and yet, through a teaching affiliation with the Massachusetts Institute of Technology (MIT), offer all the intellectual, collegial, and scientific benefits of a leading Isolated key genes involved in diabetes, research university. hypertension, leukemia, and obesity. (Lodish) WHITEHEAD INSTITUTE TODAY True to its founding vision, the Institute gives outstanding investigators broad freedom Mapped and cloned the male- to pursue new ideas, encourages novel collaborations among investigators, and determining Y chromosome, revealing a accelerates the path of scientific discovery. Research at Whitehead Institute is unique self-repair mechanism. (Page) conducted by 22 principal investigators (Members and Fellows) and approximately 300 visiting scientists, postdoctoral fellows, graduate students, and undergraduate Developed a method for genetically students from around the world. Whitehead Institute is affiliated with MIT in its engineering salt- and drought-tolerant teaching activities but wholly responsible for its own research programs, governance, plants. (Fink) and finance. Developed the first comprehensive cellular LEADERSHIP network describing how the yeast Whitehead Institute is guided by a distinguished Board of Directors, chaired by Sarah genome produces life.