News

He Yin and Murat Arcak win 2019-20 Brockett-Willems Outstanding Paper Award

EECS Prof. Murat Arcak and his graduate student He Yin have won the second Systems & Control Letters (SCL) Brockett-Willems Outstanding Paper Award. Their paper, "Reachability analysis using dissipation inequalities for uncertain nonlinear systems," published in SCL Volume 142, on August 2020, was deemed the best of 295 papers submitted to the journal in the two-year period between January 2019 through December 2020.  Co-authors include former ME Prof. Andrew Packard, who died in 2019, and Packard's former graduate student, Peter Seiler.  SCL hopes to present the award at the 25th International Symposium on Mathematical Theory of Networks and Systems (MTNS) which will be held in Bayereuth, Germany, in September 2022.

Rose Abramson wins EPE 2021 Young Author Best Paper Award

EECS graduate student Rose A. Abramson (advisor:  Robert Pilawa-Podgurski) has won the European Power Electronics and Drives Association (EPE) 2021 Young Author Best Paper Award.   Her paper, “A High Performance 48-to-8 V Multi-Resonant Switched-Capacitor Converter for Data Center Applications,” co-authored by EECS alumnus Zichao Ye (Ph.D. '20) and Prof. Robert Pilawa-Podgurski, was presented during the EPE 2020 ECCE Europe conference.  Abramson, whose research focuses on power electronics and energy, received her B.S. in 2015 and her M.Eng. in 2016, both from MIT, and worked as a project electronics engineer at both Nucleus Scientific and Lutron Electronics before coming to Berkeley.   EPE Awards honor outstanding achievements in power electronics and more generally in the field of EPE activities.

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!

Zichao Ye presents PELS Ph.D. Thesis Talk

EECS graduate student Zichao Ye (advisor: Robert Pilawa-Podgurski) is among five winners selected by the IEEE Power Electronics Society (PELS) to showcase their Ph.D. projects to the global power electronics community.  Ye's thesis, titled "Hybrid Switched-Capacitor Power Converters: Fundamental Limits and Design Techniques," focuses on a topological effort to drastically improve the performance of existing power electronics using a hybrid approach, in which both inductors and capacitors are used in the voltage conversion and power transfer process.  During his presentation in April, Ye highlighted one of his hybrid converter designs:  a 48V-to-12V cascaded resonant converter for more efficient data center which demonstrated 99% peak system efficiency and 2500 W/in3 power density.  PELS Thesis (P3) Talk Award winners are chosen by the PELS Education Digital Media Committee during an annual competition.

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.