News

The Berkeley Campus is Open

Visit the UC Berkeley COVID-19 resources website for the latest testing and access information.  Cory and Soda Halls are open but we will likely have limited in-person/on-site staffing during the first two weeks of the Spring 2022 semester.  Although most classes will be conducted remotely during this time, we anticipate in-person instruction to resume on January 31st.

Berkeley EECS continues to compete in US News & World Report rankings

Once again Berkeley Electrical Engineering ranked #1, and Computer Engineering ranked #2, in the 2022 US News and World Report graduate school rankings. EE tied with MIT and Stanford as the top graduate Electrical/Electronic/Communications Engineering program in the nation, while Computer Engineering tied in second place with Stanford after MIT. The tuition for both Master’s programs at MIT and Stanford cost over $55.5K annually, while Berkeley's costs $11.4K in-state and $26.5 out-of-state per year. Berkeley was ranked as the third best Engineering school overall.

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Laura Waller balances work, life, research, and family in a feature by the Chan Zuckerberg Initiative

EECS Prof. Laura Waller is the subject of a feature by the Chan Zuckerberg Initiative titled, “A Day in the Life of an Imaging Scientist: Laura Waller.” In it, Prof. Waller describes her day-to-day while she juggles raising a family, cultivating creativity and collaboration in her labs, and mentoring her graduate students through the pandemic. Waller is known for her work in computational imaging. In 2021, she was elected a Fellow of The American Institute for Medical and Biological Engineering (AIMBE) for her work in computational microscopy. In the same year, she won the Adolph Lomb Medal presented by Optica (formerly the Optical Society of America). “I really love this field, because it’s very creative. There are new ideas and new things to think about all the time, but it’s also grounded in real applications.”

Rod Bayliss and Vivek Nair win 2022 Hertz Fellowships

EECS graduate students Roderick Bayliss III (advisor: Robert Pilawa-Podgurski) and Vivek Nair (advisor: Dawn Song) have been selected to receive 2022 Hertz Fellowships.  One of the most prestigious awards of its kind, Hertz Fellowships support PhD students whose research show "the greatest potential to tackle society's most urgent problems." Bayliss is developing more efficient and power-dense types of power converters—devices that change the current, voltage or frequency of electrical energy—and inductors, which store energy, to help reduce the world’s dependence on fossil fuels. He earned his B.S. and M.Eng. in Electrical Engineering from MIT.  Nair is developing cutting-edge cryptographic techniques to defend digital infrastructure against sophisticated cyberthreats. He was the youngest-ever recipient of a B.A. and Master's in computer science from the University of Illinois Urbana-Champaign, and is the founder of Multifactor.com.  Their fellowships will fund up to five years of graduate research with "the freedom to pursue innovative ideas wherever they may lead."  Hertz Fellows also receive lifelong professional support, including mentoring and networking with a powerful community of more than 1,200 researchers.

Shiekh Zia Uddin wins 2022 MRS Graduate Student Gold Award

EECS graduate student Shiekh Zia Uddin (advisor: Ali Javey) has won a Materials Research Society (MRS) 2022 Graduate Student Gold Award.  These awards recognize "students of exceptional ability who show promise for significant future achievement in materials research."  Uddin works in the areas of photophysics and optoelectronics of low dimensional semiconductors, with a focus on the photophysics of low-dimensional excitonic materials.  He was honored for research which demonstrated that two-dimensional monolayer semiconductors can be defective yet perfectly bright.   The award, which comes with comes with a $400 prize, will be presented at the 2022 MRS Fall Meeting in November.

Amanda Jackson, Samantha Coday, Kelly Fernandez, and Rose Abramson win IEEE APEC best presentation awards

Four EECS students in Robert Pilawa-Podgurski's lab have won best presentation awards for papers they presented at the 2022 IEEE Applied Power Electronics Conference (APEC) in March.  Three Technical Lecture Awards were won by:  undergraduate EECS student Amanda Jackson for "A Capacitively-Isolated Dual Extended LC-Tank Converter with 50% Two-Phase Operation at Even Conversion Ratios;" graduate student Samantha Coday for "Design and Implementation of a (Flying) Flying Capacitor Multilevel Converter;" and graduate student Kelly Fernandez for "A Charge Injection Loss Compensation Method for a Series-Stacked Buffer to Reduce Current and Voltage Ripple in Single-Phase Systems."  Graduate student Rose Abramson won a Technical Dialogue Award for "Core Size Scaling Law of Two-Phase Coupled Inductors — Demonstration in a 48-to-1.8 V MLB-Pol Converter."   The Technical Sessions showcased the best, peer-reviewed papers that described "new design ideas" and "innovative solutions" in "all areas of technical interest for the practicing power electronics professional." The dialogue sessions concentrated on papers "with a more specialized focus."  APEC is the premier conference in the field of power electronics.

Alisha Menon wins 2022 Outstanding Graduate Peer Mentor Award

EECS Ph.D. candidate Alisha Menon (M.S. '20, advisor: Jan Rabaey) has won a 2022 Outstanding Graduate Peer Mentor Award.  This award, presented by The Graduate Assembly, honors four Berkeley graduate and professional students annually "who have shown an outstanding commitment to mentoring, advising, and generally supporting either undergraduate students or their fellow graduate students."  Menon's research is in the area of neural engineering, an interdisciplinary field centered on the interface between humans and computers.  Her focus is on digital integrated circuits and systems for biomedical applications, specifically the intersection of hardware-efficient machine learning algorithms, physiological sensor fusion, gesture recognition, and closed-loop neural prosthetic feedback.  Menon won an NSF Graduate Research Fellowship and UC Berkeley Fellowship in 2018.  She is also an accomplished theater actress and Indian Classical dancer.

Aviral Kumar, Serena Wang and Eric Wallace win 2022 Apple Scholars in AI/ML PhD fellowships

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.

‘Off label’ use of imaging databases could lead to bias in AI algorithms, study finds

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.”

Tiny switches give solid-state LiDAR record resolution

A new type of high-resolution LiDAR chip developed by EECS Prof. Ming Wu could lead to a new generation of powerful, low-cost 3D sensors for autonomous cars, drones, robots, and smartphones. The paper, which appeared in the journal Nature, was co-authored by his former graduate students Xiaosheng Zhang (Ph.D. '21) and Johannes Henriksson (Ph.D. '21), current graduate student Jianheng Luo, and postdoc Kyungmok Kwon, in the Berkeley Sensor and Actuator Center (BSAC).  Their new, smaller, more efficient, and less expensive LiDAR design is based on a focal plane switch array (FPSA) with a resolution of 16,384 pixels per 1-centimeter square chip, which dwarfs the 512 pixels or less currently found on FPSA.  The design is scalable to megapixel sizes using the same complementary metal-oxide-semiconductor (CMOS) technology used to produce computer processors.   Additionally, large, slow and inefficient thermo-optic switches are replaced by microelectromechanical system (MEMS) switches, which are traditionally used to route light in communications networks.  If the resolution and range of the new system can be improved, conventional CMOS production technology can be used to produce the new, inexpensive chip-sized LiDAR.

Lucas Spangher brings musicians together for Ukraine benefit concert

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.