CS undergraduate student Chase Norman is among 200 young mathematics and computer science researchers selected from across the globe to attend the 9th Heidelberg Laureate Forum (HLF) in Germany this September. During the week-long conference, participants will share ideas with some of the "most exceptional mathematicians and computer scientists of their generations," namely the recipients of some of the field’s most prestigious awards: the Abel Prize, ACM A.M. Turing Award, ACM Prize in Computing (won this year by Berkeley CS Prof. Pieter Abbeel), Fields Medal, and Nevanlinna Prize. Participants and laureates will interact through a blend of scientific and social activities that are designed to foster a relaxed atmosphere and encourage scientific exchange.  Participants are selected by a panel of international reviewers on the basis of their research experience, social engagement skills, and letter of motivation.”. Norman is a CS and Math double major who was admitted to the EECS Honors Program in the breadth area of Mathematical Logic and Foundations.  He is also the president of the CS honor society Upsilon Pi Epsilon, was course staff for CS 170 and CS 61A, and was a percussionist with UC Jazz and the UCB Symphony Orchestra.

CS graduate student Dave Epstein (advisor: Alexei Efros) has won a 2022 Paul & Daisy Soros Graduate Fellowship for New Americans.  This fellowship recognizes outstanding graduate students who are immigrants and children of immigrants in the United States, and "who are poised to make significant contributions to US society, culture or their academic field."  Epstein is affiliated with the Berkeley AI Research (BAIR) Lab where he is teaching machines to solve visual problems without labels, and enabling a creative understanding of the real world to emerge. He is also interested in language, machine learning, synthesis, and interaction. Paul & Daisy Fellowships come with a $90K award.

Three EECS graduate students, Aviral Kumar (advisor: Sergey Levine), Serena Wang (advisors: Rediet Abebe and Michael Jordan), and Eric Wallace (advisors: Dan Klein and Dawn Song) have been named 2022 recipients of the Apple Scholars in AI/ML PhD fellowship.  This fellowship recognizes graduate and postgraduate students in the field of Artificial Intelligence and Machine Learning who are "emerging leaders in computer science and engineering" as demonstrated by their "innovative research, record as thought leaders and collaborators, and commitment to advance their respective fields."  Kumar is working in the area of "Fundamentals of Machine Learning" to develop "reinforcement learning algorithms and tools that enable learning policies by effectively leveraging historical interaction data and understanding and addressing challenges in using RL with deep neural nets." Wang is working in the area of "AI for Ethics and Fairness" to "foster positive long-term societal impact of ML by rethinking ML algorithms and practices, employing tools from robust optimization, constrained optimization, and statistical learning theory."  Wallace is working in the area of "Privacy Preserving Machine Learning," to make "NLP models more secure, private, and robust." Apple Scholars receive support for their research, internship opportunities, and a two-year mentorship with an Apple researcher in their field.

A paper with lead author EECS postdoc Efrat Shimron and co-authors EECS graduate student Ke Wang, UT Austin professor Jonathan Tamir (EECS PhD ’18), and EECS Prof. Michael Lustig shows that algorithms trained using "off-label" or misapplied massive, open-source datasets are subject to integrity-compromising biases.  The study, which was published in the Proceedings of the National Academy of Sciences (PNAS), highlight some of the problems that can arise when data published for one task are used to train algorithms for a different one.  For example, medical imaging studies which use preprocessed images may result in skewed findings that cannot be replicated by others working with the raw data.  The researchers coined the term “implicit data crimes” to describe research results that are biased because algorithms are developed using faulty methodology. “It’s an easy mistake to make because data processing pipelines are applied by the data curators before the data is stored online, and these pipelines are not always described. So, it’s not always clear which images are processed, and which are raw,” said Shimron. “That leads to a problematic mix-and-match approach when developing AI algorithms.”

CS graduate student Chandan Singh (advisor: Bin Yu) has made it to the semi-finals of the 2022 Berkeley Grad Slam Competition, a UC showcase for graduate student research presented in three-minute talks for a general audience, likened to short Ted Talks.  In "Unlocking Scientific Secrets by Distilling Neural Networks," Singh hopes to build on recent advances in machine learning to improve the world of healthcare.   His research focuses on how to build trustworthy machine-learning systems by making them more interpretable through partnerships with domain experts (e.g. medical doctors and cell biologists). These collaborations give rise to useful methodology that both build more transparent models as well as improve the trustworthiness of black-box models. He hopes to help bridge the gap between both types of models so that they can be reliably used to improve real-world healthcare.

CS graduate student Lucas Spangher (advisor: Costas Spanos) gathered musicians from all over the Bay Area to perform a benefit concert in support of Ukraine on March 13th.  Opera and gospel singers, violists, pianists and harpists, were among the more than one dozen volunteers to participate in the Benefit Concert for Humanitarian Aid for Ukraine at Herbst Hall in San Francisco.  Spangher, who plays the cello, reached out to other local musicians on social media to ask if anyone would be interested in participating in an informal, online musical performance in honor of Ukraine, and it expanded from there. “It turned into this amazing professional operation,” said Spangher, “which I think just speaks to the energy and communal desire to do something. This is more than just a fundraiser. It’s a political statement and a way to honor Ukraine’s amazing contributions to classical music that can’t be erased by a vicious autocrat.”  Spangher is a committed climate change activist whose research focuses on how to make artificial intelligence become more flexible for a transition to green energy.  All proceeds from the performance have been donated to Nova Ukraine.

Students in the Data Science Discovery Program are filling a gap in engineering resources to help journalists more easily sort through large stores of records for their research.  The Discovery Program, which is part of Berkeley's Division of Computing, Data Science, and Society (CDSS), connects  around 200 undergraduates with hands-on, team-based data science research projects at Berkeley, government agencies, community groups, and entrepreneurial ventures.  Students have worked on projects like the SF Chronicle's air quality map, the Wall Street Journal's effort to analyze its source and topic diversity using natural processing language, and the California Reporting Project's police misconduct database. “I don’t know if we’d be able to do this without them,” said KQED data reporter Lisa Pickoff-White. “None of these newsrooms would be able to automate this work on their own.”

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.

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."