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.

‘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.

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.

Tsu-Jae King Liu

Tsu-Jae King Liu says the U.S. must revitalize semiconductor education and training

EECS Prof. and dean of Engineering Tsu-Jae King Liu has written an opinion piece for the Mercury News in which she explains why "the country urgently needs to reinvest in semiconductor design and manufacturing, including the development of a highly trained workforce."  She argues that America's lack of a skilled semiconductor manufacturing workforce, in the face of a global semiconductor chip shortage, is a matter of national security because it leaves the country vulnerable to geopolitical instability. "Systems that we rely upon for communications, commerce, defense and more are in jeopardy because the United States has lost its leadership in semiconductor manufacturing over the past three decades."  She appeals to Congress to address the issue and says "we need to double the number of students trained in microelectronics graduating today from all U.S. colleges and universities."  This will require "universities across the nation to collaborate with each other and to partner with industry" to create a geographically-distributed American Semiconductor Academy "with participating schools sharing curricula, facilitating access to industry-leading software tools and coordinating hands-on training for students."

Google Doodle honors Lotfi Zadeh, father of fuzzy logic

EECS Prof. Emeritus Lotfi Zadeh (1921 - 2017) is being honored with a Google Doodle feature today.  In 1964, Zadeh conceived a new mathematical concept called fuzzy logic which offered an alternative to rigid yes-no logic in an effort to mimic how people see the world.  He proposed using imprecise data to solve problems that might have ambiguous or multiple solutions by creating sets where elements have a degree of membership. Considered controversial at the time, fuzzy logic has been hugely influential in both academia and industry, contributing to, among other things, "medicine, economic modelling and consumer products such as anti-lock braking, dishwashers and elevators."   Zadeh's seminal paper, "Fuzzy Sets -- Information and Control," was submitted for publication 57 years ago today.

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.

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.

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Boubacar Kanté publishes paper introducing additional control knob for optical phase engineering

EECS Associate Prof. Boubacar Kanté is among the authors of a paper published in the journal Science titled "Plasmonic topological metasurface by encircling an exceptional point."  The paper introduces "an additional degree of freedom to address optical phase engineering by exploiting the topological features of non-Hermitian matrices operating near [the] singular points".   The novel phase, which was shown to be topologically protected, enables the construction of novel polarization dependent and chiral phased arrays and holograms. The ease of implementation together with its compatibility with other phase-addressing mechanisms will enable information multiplexing with antenna arrays.

Hani Gomez, Ph.D.: Computing Pedagogy at the Nexus of Technology and Social Justice

EECS alumna Hani Gomez (Ph.D. '20, advisor: Kris Pister) is the subject of a Berkeley Computing, Data Science, and Society (CDSS) profile titled "Hani Gomez, Ph.D.: Computing Pedagogy at the Nexus of Technology and Social Justice."  Gomez was born in Bolivia and earned her B.S. in EE at the University of South Carolina before coming to Berkeley for her graduate studies.  She has merged social justice and technology into a post-doc research position at Berkeley, split between EECS and the Human Contexts and Ethics (HCE) program in CDSS.  Gomez helped develop the course CS 194-100 EECS for All: Social Justice in EECS last spring, was one of three presenters in a June HCE workshop titled "Towards Social Justice in the Data Science Classroom," and serves on the EECS Anti-Racism Committee.  She says the preoccupation with perfectionism at Berkeley "doesn’t leave room [for you] to learn from your mistakes...You need to give yourself room to learn or unlearn, to grow and relearn.”

Yang You receives honorable mention for ACM SIGHPC Dissertation Award

EECS alumnus Yang You (Ph.D. '20, advisor: James Demmel)  was named as one of two honorable mentions for the 2020 ACM Special Interest Group in High Performance Computing (SIGHPC) Dissertation Award.  You was selected for developing LARS (Layer-wise Adaptive Rate Scaling) and LAMB (Layer-wise Adaptive Moments for Batch training) to accelerate machine learning on HPC platforms. His thesis, “Fast and Accurate Machine Learning on Distributed Systems and Supercomputers,” focuses on improving the speed and accuracy of Machine Learning training to optimize the use of parallel programming on supercomputers.  You made the Forbes 30 Under 30 2021 Asia list for Healthcare and Science in April and is now a Presidential Young Professor of Computer Science at the National University of Singapore.