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.

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."

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.

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."

"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.

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.