News

2022 Diversity in Tech Symposium: Advancing Climate Resilience - March 10-11th

A number of EECS faculty and students are slated to participate in the 2022 Diversity in Tech Symposium, which will be held virtually on March 10 & 11.  This year's theme is "Advancing Climate Resilience."  EECS Prof. Tsu-Jae King Liu, dean of Berkeley Engineering, will warm up the audience with a fireside chat on the symposium's topic;  EECS Prof. Costas Spanos, director of the CITRIS and Banatao Institute, will welcome participants to the second day of the event;  Adjunct Prof. Sascha von Meier will participate in the UC Berkeley-hosted panel Getting to zero: Trends in the built environment; and senior EECS major Katherine Shu will represent WiCSE in a presentation on the Career Fair.  The symposium is open to the public and anyone interested in climate innovation and action, and the advancement of women and underrepresented communities working in technology fields, is encouraged to attend.

CDSS and Cal Performances present: "Place and Displacement: Bias in Our Algorithms and Society"

The Division of Computing, Data Science, and Society (CDSS) is excited to announce an upcoming event in collaboration with Cal Performances. On October 28, "Place and Displacement: Bias in Our Algorithms and Society" will feature Cal Artist-in-Residence Angélique Kidjo in conversation with CDSS Associate Provost Jennifer Chayes, EECS Assistant Professor Nika Haghtalab and Computer Science PhD Student Devin Guillory (advisor: Trevor Darrell). The group will discuss the intersection of artificial intelligence and art, computing tools' reflection of the biases of the people and data used to train them, and promising interventions that could make algorithms more just.  The event, which is free and open to the public, will be held in person at Zellerbach Hall from 4:00 to 5:30 pm PST on Thursday, October 28. It will also be live-streamed. Registration is required and now open!

Anca Dragan, Raluca Popa, and Thomas Courtade win 2020 EECS Teaching Awards

The 2019-20 EECS Teaching Awards recognize three members of our faculty whose extraordinary performances kept students focused and engaged during a particularly difficult year.  The CS Diane McEntyre Award for Excellence in Teaching was presented to Anca Dragan in the spirit of McEntyre who was know for her "dedication to teaching and her innovative programs for women in mathematics and computer science." Students said Dragan was "passionate, dedicated, inclusive, and enthusiastic," and "literally the most entertaining and helpful professor I’ve ever had." The CS Jim and Donna Gray Faculty Award for excellence in undergraduate teaching went to Raluca Ada Popa. She was commended by students for her passion, clarity, care, and enthusiasm, and was described as an "AMAZING" and entertaining lecturer who "encourages a lot of class discussion and gets us involved, even over zoom."   The EE Award for Outstanding Teaching, which recognizes innovation and excellence in curriculum and teaching methods, publication of quality textbooks, graduate and undergraduate advising, and personal inspiration of students, was presented to Thomas Courtade.  He was described by students as "a brilliant instructor" whose "ability to teach the fundamental core concepts of this content is incredible." He was also said to be "amazing when it comes to interacting with students. It is hard to believe how many people are in the class, because he makes it feel very personal."

Matthew Anderson wins 2021-22 Google-CMD-IT LEAP Fellowship Award

EECS Ph.D. student Matthew Anderson (advisors: Jan Rabaey and Ali Niknejad) has won the Google-CMD-IT LEAP Fellowship Award for 2021-22.  The award recognizes computer science scholars from underrepresented groups who are "positively influencing the direction and perspective of technology."  Anderson, who also won the 2021 Berkeley EECS Eugene L. Lawler Prize, has been a pioneer in the department's anti-racism efforts, including taking a leadership position in the EECS and Division of Computing, Data Science, and Society (CDSS) faculty/staff/student Anti-Racism Committee. His research interests include design of mixed-signal and wireless circuits for bio-sensing, brain machine interfaces, and accelerated neural networks.  This award is part of a joint effort by Google Research, the Computing Alliance of Hispanic-Serving Institutions (CAHSI), and the Center for Minorities and People with Disabilities in Information Technology (CMD-IT) Diversifying LEAdership in the Professoriate (LEAP) Alliance to increase the diversity of doctoral graduates in computing.  Anderson is one of three winners of this year's award. Last year's inaugural award was won by EECS grad student Gabriel Fierro.

Sagnik Bhattacharya and Jay Shenoy named 2022 Siebel Scholars

Graduate students Sagnik Bhattacharya (B.A. CS and Statistics '21) and Jay Shenoy (B.A. CS '21) are recipients of the 2022 Siebel Scholars award.  The Siebel Scholars program annually recognizes "exceptional students from the world’s leading graduate schools of business, computer science, and bioengineering."  Bhattacharya, a 5th Year Masters student and TA for CS 70 (Discrete Math and Probability), is interested in machine learning theory and its applications in data science.  He is currently working with Prof. Jonathan Shewchuk on the theory behind deep linear neural networks.  Shenoy is working on computational imaging with Prof. Ren Ng, as well as problems in autonomous vehicle simulation in the Industrial Cyber-Physical Systems (iCyPhy) group.  Siebel Scholars receive a $35,000 award for their final year of studies. "On average, Siebel Scholars rank in the top five percent of their class, many within the top one percent."

Sam Kumar

Sam Kumar wins OSDI Jay Lepreau Best Paper Award

CS graduate student Sam Kumar (advisors: David Culler and Raluca Ada Popa) has won the Jay Lepreau Best Paper Award at the 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI) for "MAGE: Nearly Zero-Cost Virtual Memory for Secure Computation."   The OSDI, which brings together "professionals from academic and industrial backgrounds in a premier forum for discussing the design, implementation, and implications of systems software," selects three best papers each year after a double-blind review.  Co-authored by Prof. David Culler and Associate Prof. Raluca Ada Popa, the paper introduces an execution engine for secure computation that efficiently runs computations that do not fit in memory.  It demonstrates that in many cases, one can run secure computations that do not fit in memory at nearly the same speed as if the underlying machines had unbounded physical memory to fit the entire computation.  Kumar works in the Buildings, Energy, and Transportation Systems (BETS) research group in the RISE Lab.

Deanna Gelosi wins Best Full Paper Award at ACM IDC 2021

"PlushPal: Storytelling with Interactive Plush Toys and Machine Learning," co-authored by CS Masters student Deanna Gelosi (advisor: Dan Garcia), has won the Best Full Paper Award at the Association for Computing Machinery (ACM) Interaction Design for Children (IDC) conference 2021.  IDC is "the premier international conference for researchers, educators and practitioners to share the latest research findings, innovative methodologies and new technologies in the areas of inclusive child-centered design, learning and interaction."  The paper, which was presented in the "Physical Computing for Learning" conference session, describes PlushPal, "a web-based design tool for children to make plush toys interactive with machine learning (ML). With PlushPal, children attach micro:bit hardware to stuffed animals, design custom gestures for their toy, and build gesture-recognition ML models to trigger their own sounds."  It creates "a novel design space for children to express their ideas using gesture, as well as a description of observed debugging practices, building on efforts to support children using ML to enhance creative play."  Gelosi's degree will be in the field of Human-Computer Interaction and New Media, and her research interests include creativity support tools, traditional craft and computing technologies, digital fabrication, and equity in STEAM.  She is a member of the Berkeley Center for New Media (BCNM), the Berkeley Institute of Design (BID), and the Tinkering Studio--an R&D lab in the San Francisco Exploratorium.

New AI system allows legged robots to navigate unfamiliar terrain in real time

A new AI system, Rapid Motor Adaptation (RMA), enhances the ability of legged robots, without prior experience or calibration, to adapt to, and traverse, unfamiliar terrain in real time.  A test robot figured out how to walk on sand, mud, and tall grass, as well as piles of dirt, pebbles, and cement, in fractions of a second.  The project is part of an industry-academic collaboration with the Facebook AI Research (FAIR) group and the Berkeley AI Research (BAIR) lab that includes CS Prof. Jitendra Malik as Principal Investigator, his grad student Ashish Kumar as lead author, and alumnus Deepak Pathak (Ph.D. 2019, advisors: Trevor Darrell and Alexei Efros), now an assistant professor at Carnegie Mellon, among others.  RMA combines a base policy algorithm that uses reinforcement learning to teach the robot how to control its body, with an adaptation module that teaches the robot how to react based on how its body moves when it interacts with a new environment.  “Computer simulations are unlikely to capture everything,” said Kumar. “Our RMA-enabled robot shows strong adaptation performance to previously unseen environments and learns this adaptation entirely by interacting with its surroundings and learning from experience. That is new.”  RMA's base policy and adaptation module run asynchronously and at different frequencies so that it can operate reliably on a small onboard computer.  

NLP team helps a computer win the 2021 American Crossword Puzzle Tournament

A team at the Berkeley Natural Language Processing Group (NLP) helped augment an AI system named "Dr. Fill" that has won the 2021 American Crossword Puzzle Tournament (ACPT).  This is the first time in the contest's history that an AI has trumped its human competitors.  The team, which included CS Prof. Dan Klein, graduate students Nicholas Tomlin, Eric Wallace, and Kevin Yang, and undergraduate students Albert Xu and Eshaan Pathak, approached Matthew Ginsberg, who created the Dr. Fill algorithm in 2012, and offered to join forces by contributing their machine learning system  called the Berkeley Crossword Solver (BCS).  BCS employs a neural network model to combine general language understanding with more "creative" crossword puzzle clues, then applies its knowledge to practice puzzles, improving as it learns.  “We had a state-of-the-art natural language understanding and question-answering component but a pretty basic crossword handler, while Matt had the best crossword system around and a bunch of domain expertise, so it was natural to join forces,” said Klein. “As we talked, we realized that our systems were designed in a way that made it very easy to interoperate because they both speak the language of probabilities.”  ACPT is the oldest and biggest tournament of its kind, consisting of seven qualifying puzzles and a final playoff puzzle; solvers are ranked using a formula that balances accuracy and speed. Although Dr. Fill made three errors, it completed most puzzles in well under a minute, and ultimately outscored its top human competitor, who made zero errors, by 15 points.  The contest was held online this year and attracted more than 1,100 contestants vying for the $3K grand prize. 

EECS Faculty votes to drop GRE requirement indefinitely

After intensive debate spanning 2020 and 2021, and careful analysis of a trial cycle of GRE-free admissions for Fall 2021, the EECS Department has voted to drop the GRE requirement for graduate admissions indefinitely. Effective immediately, and beginning with the Fall 2022 cohort, whose application window opens in September 2021, the application requirements for all graduate research degree programs in EECS will neither require, nor accept, GRE scores.

In 2020, at the onset of the pandemic, the EECS faculty temporarily suspended the GRE requirement for graduate admissions for the 2020-21 cycle, i.e., for those admitted for Fall 2021, primarily due to the challenges posed by COVID. The department subsequently observed a 30% increase in applications from groups historically underrepresented in EECS, a 47% increase in admittance of those applicants, and a 150% increase in yield from those populations. Not only did we attract and admit more high-performing underrepresented students, but a higher percentage of those admitted decided to attend UC Berkeley to study EECS.

The graduate admissions process in EECS is a holistic review involving the following factors: transcripts, letters of recommendation, personal statements, statements about intended research, publications (if any), and for applicants evaluated favorably on these factors, one or more phone conversations with EECS faculty.  Since applicants come from a wide range of socioeconomic and educational backgrounds, we also consider the applicant's demonstrated ability and motivation taken in the context of the opportunities they had available. Given this thorough, multifaceted review, the majority of EECS faculty concluded, after extensive discussion, that the GRE does not add much value, relative to the harm it does to diversity and equity. 

Diversity in science, technology, engineering and mathematics (STEM) fields is a longstanding challenge. For example, nationally, fewer than 22% of computer science PhD degrees are awarded to women students, and only 4% to Black students. GRE scores show significant gender and race-based differences, but these differences do not correlate with later success in graduate school, much less with undergraduate grade point average (GPA) in many cases. Therefore, using GRE scores as a “cutoff” disadvantages women and underrepresented minorities applying to graduate programs. The UC Regents recently voted to drop ACT/SAT scores from undergraduate admissions for the UC system for similar reasons.

For these reasons, along with the financial burden GRE testing fees place on economically disadvantaged applicants across the globe, the EECS Department has concluded that the GRE score has limited benefit in evaluating PhD and masters degree applicants, and that the exam itself, as well as the administration of it, harms diversity and equity.

For more information about Berkeley EECS graduate admissions, please visit our website: 

https://eecs.berkeley.edu/academics/graduate/research-programs/admissions