News

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(Photo by Adam Lau/Berkeley Engineering)

Berkeley EECS faculty to join NSF-backed AI cybersecurity institute

Five Berkeley EECS faculty members have joined the newly formed AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION), which is backed by the National Science Foundation (NSF). NSF will invest $140 million into seven new National Artificial Intelligence Research Institutes, of which ACTION is a key institute that will use AI to address risks in cybersecurity. The UC Berkeley team will be led by CS Professor Dawn Song, as well as Professors Stuart Russell, Pieter Abbeel, David Wagner, and Bin Yu. “UC Berkeley’s team aims to develop both new foundational technologies in learning and reasoning, as well as their novel applications in the cybersecurity domain, to significantly improve state-of-the-art technologies throughout the life cycle of cyber defense,” said Song.

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Gireeja Ranade and Sophia Shao win NSF CAREER Awards

The National Science Foundation (NSF) awarded two EECS assistant professors, Gireeja Ranade and Sophia Shao, with Faculty Early Career Development (CAREER) awards. The awards are part of NSF's prestigious CAREER Program, which supports early-career faculty “who have the potential to serve as academic role models” and leaders in their field. Ranade received a grant of $422,181 to explore new non-linear control strategies, while Shao received a grant of $600,000 to fund her work on improving the performance of computing platforms.

William Kahan raising a glass in celebration of IEEE Standard 754
(Photo: Berkeley EECS)

IEEE Standard 754 Milestone Dedication honors William Kahan

A dedication ceremony was held to honor EECS Emeritus Professor William Kahan for his contribution to the development of IEEE Standard 754. The ceremony, which took place on Wednesday, May 3rd, included remarks from Dean Liu, Chair Tomlin, and CS Professor Jim Demmel. A new commemorative plaque was unveiled in Soda Hall, next to the IEEE plaque that celebrates Berkeley EECS’ contribution to RISC. The new plaque celebrates Kahan and others’ work in the development of IEEE Standard 754, which was originally conceived in 1978. Kahan and his colleagues revolutionized numerical computing, creating arithmetic and standard data types that improved software reliability and portability. The IEEE 754 standard is widely used for numerical computing and is still being improved today.

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Gireeja Ranade honored for outstanding mentorship of GSIs

EECS Teaching Professor Gireeja Ranade has received the Faculty Award for Outstanding Mentorship of GSIs. The annual award, which is sponsored by the Graduate Council’s Advisory Committee for GSI Affairs and the GSI Teaching & Resource Center, recognizes faculty who have provided GSIs outstanding teaching and pedagogical mentorship at Berkeley and in preparing for teaching in future careers.

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Berkeley EECS graduate programs lead US News Rankings

The U.S. News & World Report ranked both the Electrical Engineering and Computer Science graduate programs at Berkeley EECS among the top three graduate programs in the nation for 2023. Computer Science is ranked #1, tied with MIT and Stanford. Electrical Engineering and Computer Engineering are ranked #2, tied with Stanford. The magazine based its rankings on responses from 202 engineering schools across the country, including data from fall 2022 and early 2023. This year, U.S. News included non-responders from the 220 schools surveyed, so long as they reported enough data to be eligible in 2022.

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Venkatesan Guruswami wins 2022 Guggenheim Fellowship

CS Professor Venkatesan Guruswami has won the 2023 Guggenheim Fellowship for his research proposal on mathematical computer science titled, “Mathematical Structure and Efficient Algorithms:  The Polymorphic Gateway.” The fellowship is awarded by the John Simon Guggenheim Memorial Foundation on the basis of "prior achievement and exceptional promise." Professor Guruswami is a Chancellor’s Professor and a senior scientist at the Simons Institute for the Theory of Computing. “I’m really delighted and grateful to be chosen for this Fellowship, and honored to join its distinguished roster of past recipients,” said Guruswami.

Jelani Nelson receives ACM-SIGACT Distinguished Service Award

CS Professor Jelani Nelson has won the Association for Computing Machinery Special Interest Group for Algorithms and Computation Theory (ACM-SIGACT) Distinguished Service Award. Nelson was cited “for outstanding contributions to broadening participation in computer science, and in theoretical computer science in particular.” Awarded annually, the SIGACT Distinguished Service Award is given to those who have made "substantial contributions to the Theoretical Computer Science community.” Nelson founded AddisCoder, a summer program that aims to introduce high school students in developing countries to the fundamentals of computational thinking. The program, which began in Ethiopia, has educated more than 500 students and has recently extended to Jamaica. Nelson also co-founded the David Harold Blackwell Summer Research Institute, whose internship opportunities serve undergraduates across the U.S. with the goal of increasing African American students that pursue graduate studies in mathematical sciences.

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EECS Faculty to explore implications of ChatGPT in new AI lecture series

EECS Faculty will headline a new AI lecture series to explore the “paradigm shift” that ChatGPT and other large language models (LLMs) have catalyzed. CS Professors Jitendra Malik, Stuart Russell and Michael Jordan are among the seven speakers scheduled this spring to address the sensation that is ChatGPT and other related LLMs. CS Professor Ken Goldberg, who organized the lecture series on behalf of Berkeley Artificial Intelligence Research (BAIR), said, “Something changed very dramatically with the performance of ChatGPT, compared with previous large language models, and everyone, including experts, is asking, ‘What does it mean? Where do we go from here?’” The series will also feature John Schulman (Ph.D. ‘16; advisor: Pieter Abbeel), a co-founder of OpenAI and the primary architect of ChatGPT. “Everyone wants to hear from the experts,” Goldberg said. “There are so many misconceptions out there. In the series, we’ll hear from those who have been working in the field for many years who can provide valuable perspectives on the importance of ChatGPT.”

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(Photo by Keegan Houser)

Joshua Hug wins 2023 UC Berkeley Distinguished Teaching Award

Professor Joshua Hug has won the University of California, Berkeley Distinguished Teaching Award. Presented by the Academic Senate, the Distinguished Teaching Award (DTA) is considered UC Berkeley’s most prestigious award for teaching. The DTA recognizes individual faculty “for sustained excellence in teaching.” Recipients are among the brightest teaching stars on campus, widely recognized for their inspiring and transformational teaching. The highly selective, multi-phase nomination process seeks teachers who incite intellectual curiosity and whose teaching has a life-long impact. Only 223 faculty have received the award since its inception in 1959, including several from Berkeley EECS. Hug is known for teaching CS 61B, an introductory computer science course on data structures that regularly enrolls over 1500 students each spring. DTA  winners are frequently called upon by the campus community to provide a voice on issues related to teaching. They serve on forums, panels, and committees involving teaching issues, and they are advocates for excellence in teaching at Berkeley.

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Bin Yu wins 2023 COPSS Distinguished Achievement Award and Lectureship

The Committee of Presidents of Statistical Societies (COPSS) has selected Bin Yu, Professor of EECS and Statistics, for the 2023 Distinguished Achievement Award and Lectureship (DAAL). Formerly known as the R. A. Fisher Award and Lectureship, the DAAL recognizes meritorious achievement and scholarship in statistical science and recognizes the highly significant impact of statistical methods on scientific investigations. She will deliver the DAAL Lecture at JSM in 2023 on veridical data science. Yu’s research focuses on practice, algorithm, and theory of statistical machine learning, interpretable machine learning, and causal inference. Her group is engaged in interdisciplinary research with scientists from genomics, neuroscience, and precision medicine. She and her group have developed the predictability, computability, and stability (PCS) framework for veridical data science toward responsible, reliable, and transparent data analysis and decision-making.