Women in Computing
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Claudia Friedetzky Saturday, February 21, 10 Am Braddock Supervisor's
FOCUS February 2015 Volume 41, No. 5 Our Troubled Waters Speaker: Claudia Friedetzky Saturday, February 21, 10 a.m. Braddock Supervisor’s Office, Kings Park Library Water is our most precious resource, and Environmental Leadership program and we take it for granted that when we turn on Public Policy Fellowship program at the the tap, it's always going to be there. In Center for Women in Government. places such as California; however, supplies This is a joint meeting with the Springfield- are running dangerously low. The old Annandale branch. The Braddock struggle between the cowhands and the Supervisor’s Office is located at the back of farmers is being updated to the suburbs the Kings Park Library, 9000 Burke Lake with their golf courses and the commercial Road, Burke, near the intersection with farms that supply all of us with our food. Rolling Road. What role is climate change having in Directions: accelerating the shortages that are forecast From Braddock Road: Turn south on Burke Lake Road. Go one block. Kings Park Library will be on your right. around the globe? And what about our own From Fairfax County Parkway: Turn north on Burke Lake water supplies, both with regard to purity Road. Kings Park Library will be on your left, just past Lake Braddock Secondary School. and supply? If, as proposed, fracking is permitted in the George Washington In this issue: National Forest, what risk will that bring? Vision to Reality ......................................... 2 Why Join AAUW? ....................................... 2 Our guest, Claudia Friedetzky, a climate Book & Author Update .............................. 3 activist with the Maryland Chapter of the STEMtastics ............................................... -
Solving the Equation
SOLVING THE EQUATION The Variables for Women’s Success in Engineering and Computing EXECUTIVE SUMMARY To download a free copy of the full report, Solving the Equation: The Variables for Women’s Success in Engineering and Computing, go to www.aauw.org/what-we-do/research. More than ever before in history, girls are studying and excelling in science and mathematics. Yet the dramatic increase in girls’ educational achieve- ments in scientific and mathematical subjects has not been matched by similar increases in the representation of women working as engineers and computing professionals. Women made up just 26 percent of computing professionals in 2013, a substantially smaller portion than 25 years ago and about the same percentage as in 1960. In engineering, women are even less well represented, making up just 12 percent of working engineers in 2013. The representation of women in engineering and computing occupations matters. Diversity in the workforce contributes to creativity, productivity, and innovation. Women’s experiences—along with men’s experiences— should inform and guide the direction of engineering and technical innova- tion. We simply can’t afford to ignore the perspectives of half the population in future engineering and technical designs. Advocates have long extolled the importance of advancing girls and women in science, technology, engineering, and mathematics (STEM). WOMEN IN SELECTED STEM OCCUPATIONS, 1960–2013 60 53% 50 46% 44% 42% 39% 40 35% 35% 34% 33% 32% 28% 30 26% 27% 26% 30% 27% 20% 26% 20 20% Percentage of women of Percentage 12% 11% 11% 12% 9% 10 8% 5% 1% 2% 0 1960 1970 1980 1990 2000 2010 2013 Engineers Chemists and Computer and mathematical Biological scientists material scientists occupations Sources: AAUW analysis of data from U.S. -
From the Woman Question in Technology to the Technology Question in Feminism
05 Henwood (mh/d) (EJWS) 28/3/00 9:32 am Page 209 From the Woman Question in Technology to the Technology Question in Feminism Rethinking Gender Equality in IT Education Flis Henwood UNIVERSITY OF EAST LONDON ABSTRACT There have, by now, been a number of thorough-going critiques of what has variously been called the ‘equality’, ‘equity’ or ‘liberal’ approach to understanding ‘the woman problem in technology’ by those who would prefer to focus on ‘the technology question in feminism’. Most of these critiques adopt deconstructivist techniques to expose the limitations of equality approaches, including, most centrally, their assumptions about the neutrality of technology and the limited nature of equality programmes designed simply to increase access for women to that technology. However, the critiques themselves have so far failed to come up with convincing alternative interventionist strategies, either because the universalizing tendency of their theoretical perspective gives rise to interventions that fail to deal with the diverse and fragmented nature of women’s experiences and needs, or because recognition of this diversity and fragmentation leaves very little common ground on which to build successful intervention strategies. This article addresses this dilemma in the context of computing and IT education and draws on empirical research on women’s experiences of computing and IT in two different educational settings where issues of gender difference and equality were managed in very contrasting ways. It then offers some suggestions for how both a critical and constructivist discourse on technology might be made to coexist in educational programmes designed to promote gender equality. KEY WORDS computing ◆ education ◆ equality ◆ gender ◆ technology The European Journal of Women’s Studies Copyright © SAGE Publications (London, Thousand Oaks and New Delhi), Vol. -
1 “We Are Ewits
“WE ARE EWITS - HEAR US ROAR!”: EMPOWERING WOMEN IN TECHNOLOGY STARTUPS (EWITS) AS AN EXPERIENTIAL LEARNING MODEL TO CHALLENGE GENDERED SOCIAL NORMS IN THE FIELD By CHERYL D. CALHOUN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2017 1 © 2017 Cheryl D. Calhoun 2 To my wife and family 3 ACKNOWLEDGMENTS First, I would like to thank my wife, Ester, for her support and encouragement throughout this process. She provided many hours of reflection, including some challenging debate, about my ideas and understanding of my work. She was also patient, and incredibly supportive, when I just needed space to work things out for myself. I would also like to thank my children, Sean, and Jessica, who supported me along the way and never doubted that I would accomplish this goal. I would like to thank my Santa Fe College family. The incredible professionals at the educational centers and throughout the college who provided support and understanding while I juggled a full-time academic career along with a full-time pursuit of a PhD. I thank the faculty at the University of Florida, who challenged me in the classroom, and worked with me as I integrated my classroom learning into my years of experience in academia. I thank my committee members, Dr. Kara Dawson, Dr. Rosana Resende, and Dr. Andy Naranjo, who provided challenging feedback and pushed me to refine my thinking and align my research goals. I would like to thank my chair, Dr. -
Bluemona Jalal: Curriculum Vitae
Mona Jalal monajalal.com [email protected] AIEM BU IVC Research Interest Computer Vision, Machine Learning, Deep Learning, Vision and Language. Education Computer Science Ph.D. Fellow in Computer Vision Boston University, Boston, MA, USA. Adviser: Professor Margrit Betke GPI: 3.84 out of 4 September 2017-now Double Major M.Sc. in Computer Sciences and Electrical Engineering University of Wisconsin-Madison, Madison, WI, USA. CS GPA: 3.62, CGPA of both degrees: 3.49 out of 4 CS Master's Graduation: May 15th 2016, EE Master's Graduation: August 24th 2014 M.Sc. in Computer Engineering Majored in Computer Architecture Sharif University of Technology, Tehran, Iran. CGPA: 17.71 out of 20 B.Sc. in Computer Engineering Majored in Computer Hardware Shahid Beheshti University, Tehran, Iran. CGPA: 15.32 out of 20 Second best hardware engineering student in batch of 2009 graduates National Organization for Development of Exceptional Talents Karaj, Tehran, Iran Designated for top 5% of the entire high school students in Iran Experience Research Intern NVIDIA Research, North Carolina, Durham Mentor: Dr. Josef Spjut, collaborator: Ben Boudaoud, Manager: Dr. David Luebke June 20-August 31, 2018 R&D Engineer 1 Center for Augmented Cognition, University of California, Berkeley Under supervision of Dr. Allen Y. Yang and mentorship of Joseph Menke May 1-August 15, 2017 Research Intern Computer Vision Group, Medical Sciences Center, University of Wisconsin-Madison Under supervision of Professor Vikas Singh and mentorship of Professor Won Hwa Kim August 1, 2016-May 1, 2017 Graduate Research Assistant Internet of Things Lab, University of Wisconsin-Madison Under supervision of Dr. -
Parallel Program Graphs and Their Classi Cation
Parallel Program Graphs and their Classication Vivek Sarkar Barbara Simons IBM Santa Teresa Lab oratory Bailey Avenue San Jose CA fvivek sarkarsimonsgvnetib mcom Abstract We categorize and compare dierent representations of pro gram dep endence graphs including the Control Flow Graph CFG which is a sequential representation lacking data dep endences the Program Dep endence Graph PDG which is a parallel representation of a se quential program and is comprised of control and data dep endences and more generally the Parallel Program Graph PPG which is a parallel representation of sequential and inherently parallel programs and is comprised of parallel control ow edges and synchronization edges PPGs are classied according to their graphical structure and prop erties related to deadlo ck detection and serializabil i ty Intro duction The imp ortance of optimizing compilers has increased dramatically with the development of multipro cessor computers Writing correct and ecient parallel co de is quite dicult at b est writing such software and making it p ortable cur rently is almost imp ossible Intermediate forms are required b oth for optimiza tion and p ortability A natural intermediate form is the graph that represents the instructions of the program and the dep endences that exist b etween them This is the role played by the Parallel Program Graph PPG The Control Flow Graph CFG in turn is required once p ortions of the PPG have b een mapp ed onto individual pro cessors PPGs are a generalization of Program Dep endence Graphs PDGs which have -
WOMEN TECHNOLOGISTS COUNT Recommendations and Best Practices to Retain Women in Computing
WOMEN TECHNOLOGISTS COUNT Recommendations and Best Practices to Retain Women in Computing ANITA BORG INSTITUTE SOLUTIONS SERIES TABLE OF CONTENTS Foreword . 1 Introduction . 2 Leadership and Accountability . 5 Corporate Culture Built for Innovation . 7 Support Networks and Communities . 11 Organizational Infrastructure and Policies . 18 Conclusion . 21 Endnotes . 22 FOREWORD ver the past 15 years, as the Anita Borg Institute has worked to improve the representation and advancement of women in computing, we’ve learned how important it is to retain women in the technical Ocareer pipeline . We know from our work with organizations that turnover among women in technology is a significant problem . Companies recognize that they cannot afford to lose valuable talent, but making a tangible impact on attrition levels can be challenging . Attrition begins when some women struggle in the transition from college to their first technical position in industry . For those who stay initially, the mid level is an especially critical “make or break” point . Many mid-level women leave the technical track to become managers . Others switch companies or step away from technology altogether . Those who advance to senior technical roles face many obstacles as they work toward the top tiers of technical leadership . Keeping women in the technical workforce matters . Teams that have a diversity of perspective, including gender, improve innovation and, ultimately, financial performance . It is in the best interest of technology companies to retain women who are committed to inventing technology and making a contribution in their fields . To institute real change in the workplace, employees throughout the organization need to understand that including people with a broad range of perspective, background and gender is a business imperative . -
Female Under-Representation in Computing Education and Industry - a Survey of Issues and Interventions
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 5, No. 10, 2014 Female Under-Representation in Computing Education and Industry - A Survey of Issues and Interventions Joseph Osunde, Gill Windall, Professor Liz Bacon and Professor Lachlan Mackinnon Department of Computing and Mathematical Sciences, University of Greenwich, London, UK Abstract—This survey paper examines the issue of female Mathematics (STEM) subjects. The second section reviews under-representation in computing education and industry, the key factors which have been proffered as potential causes which has been shown from empirical studies to be a problem for for the under-representation of females in computing over two decades. While various measures and intervention education and industry. This section will further review the strategies have been implemented to increase the interest of girls key arguments and associated theories. in computing education and industry, the level of success has been discouraging. The key intervention strategies implemented which have been employed in an attempt to reverse this trend are The primary contribution of this paper is to provide an discussed in the third section of the article. A review of these analysis of the extensive research work in this area. It outlines strategies provides an opportunity to explore the breadth of the progressive decline in female representation in computing current solutions and identify areas for further investigation. education. It also presents the key arguments that attempt to explain the decline and intervention strategies. We conclude that II. EVIDENCE OF THE PROBLEM there is a need to further explore strategies that will encourage young female learners to interact more with computer A. -
Social Sciences $€ £ ¥
social sciences $€ £ ¥ Article Segregation, Stereotypes, and STEM Sarah Thébaud and Maria Charles * Department of Sociology, University of California—Santa Barbara, Santa Barbara, CA 93106-9430, USA; [email protected] * Correspondence: [email protected] Received: 10 May 2018; Accepted: 4 July 2018; Published: 9 July 2018 Abstract: Scientific, technical, engineering, and mathematical (STEM) occupations are strongholds of gender segregation in the contemporary United States. While many Americans regard this segregation as natural and inevitable, closer examination reveals a great deal of variability in the gendering of STEM fields across time, space, and demographic groups. This article assesses how different theoretical accounts accord with the available evidence on the gender composition of scientific and technical fields. We find most support for accounts that allow for a dynamic interplay between individual-level traits and the broader sociocultural environments in which they develop. The existing evidence suggests, in particular, that Western cultural stereotypes about the nature of STEM work and STEM workers and about the intrinsic qualities of men and women can be powerful drivers of individual aptitudes, aspirations, and affinities. We offer an illustrative catalog of stereotypes that support women’s STEM-avoidance and men’s STEM-affinity, and we conclude with some thoughts on policy implications. Keywords: gender; STEM; segregation; stereotypes; culture; work; occupations; science; inequality For more than three decades, American educators, policy makers, activists, and business leaders have engaged in research and policy initiatives to increase the presence of women and other underrepresented groups in scientific, technical, engineering, and mathematical (STEM) occupations and fields of study. These efforts have been motivated by interests in broadening opportunities in lucrative, high-status occupations and in ameliorating acute STEM labor shortages that are believed to threaten national prosperity, private profits and the public welfare. -
Bluemona Jalal: Curriculum Vitae
Mona Jalal monajalal.com [email protected] BU IVC Research Interests Computer Vision, Machine Learning, Deep Learning, Multimodal Learning, Vision and Language. Education Computer Science Ph.D. Candidate in Computer Vision Boston University (BU), Boston, MA, USA. Adviser: Professor Margrit Betke Ph.D. Candidacy on \3D Human's Shape, Mesh, and Modeling with Applications" Dissertation topic: Pose Estimation and Tracking Capturing video using two thermal FLIR SC8000 cameras and two HSDR devices from rodents. 3D reconstruction and 2D/3D pose estimation and behavior categorization in rodents. Exploring the use of 3D shapes for better estimation of pose. GPI: 3.85/4 September 2017-now Double Major M.Sc. in Computer Sciences and Electrical Engineering University of Wisconsin-Madison (UW), Madison, WI, USA. CS GPA: 3.62, CGPA of both degrees: 3.49 out of 4 CS Master's Graduation: May 15th 2016, EE Master's Graduation: August 24th 2014 M.Sc. in Computer Engineering Majored in Computer Architecture Sharif University of Technology (SUT){Ranked 1st in Iran CGPA: 17.71 out of 20 B.Sc. in Computer Engineering Majored in Computer Hardware Shahid Beheshti University (SBU){Ranked 5th in Iran. CGPA: 15.32 out of 20 Second best hardware engineering student in batch of 2009 graduates National Organization for Development of Exceptional Talents (NODET) Karaj, Tehran, Iran Designated for top 5% of the entire high school students in Iran Experiences Machine Learning Engineering Intern Hateful conduct detection in tweets Twitter Cortex, Cambridge, MA Mentors: Dr. Kristen Sunter and Dr. Eting Yuan, Manager: Dr. Rani Nelken June 3rd-August 30, 2019 Research Intern 3D object pose dataset creation using Unreal Engine 4 NVIDIA Research, Durham, North Carolina Mentor: Dr. -
Incremental Computation of Static Single Assignment Form
Incremental Computation of Static Single Assignment Form Jong-Deok Choi 1 and Vivek Sarkar 2 and Edith Schonberg 3 IBM T.J. Watson Research Center, P. O. Box 704, Yorktown Heights, NY 10598 ([email protected]) 2 IBM Software Solutions Division, 555 Bailey Avenue, San Jose, CA 95141 ([email protected]) IBM T.J. Watson Research Center, P. O. Box 704, Yorktown Heights, NY 10598 ([email protected]) Abstract. Static single assignment (SSA) form is an intermediate rep- resentation that is well suited for solving many data flow optimization problems. However, since the standard algorithm for building SSA form is exhaustive, maintaining correct SSA form throughout a multi-pass com- pilation process can be expensive. In this paper, we present incremental algorithms for restoring correct SSA form after program transformations. First, we specify incremental SSA algorithms for insertion and deletion of a use/definition of a variable, and for a large class of updates on intervals. We characterize several cases for which the cost of these algorithms will be proportional to the size of the transformed region and hence poten- tially much smaller than the cost of the exhaustive algorithm. Secondly, we specify customized SSA-update algorithms for a set of common loop transformations. These algorithms are highly efficient: the cost depends at worst on the size of the transformed code, and in many cases the cost is independent of the loop body size and depends only on the number of loops. 1 Introduction Static single assignment (SSA) [8, 6] form is a compact intermediate program representation that is well suited to a large number of compiler optimization algorithms, including constant propagation [19], global value numbering [3], and program equivalence detection [21]. -
Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration.