EECS Prof. Tsu-Jae King Liu has been selected to receive the 2021 IEEE Electron Devices Society (EDS) Education Award.  This award is presented annually by EDS to honor "an individual who has made distinguished contributions to education within the field of interest of the Electron Devices Society."  Liu, who is currently the dean of Berkeley Engineering, was cited “For outstanding contributions to education in the field of electron devices and achievements on diversity and inclusion.”  She has been a strong advocate for fostering inclusion and respect for women and members of underrepresented minorities in engineering.  She was the first woman to Chair the EECS department (2014), the second woman to join Intel's board of directors (2016), and the first woman elected dean of the Berkeley College of Engineering (2018).  She won the Chang-Lin Tien Leadership in Education Award in 2020.   Liu is also renowned for her research into novel semiconductor devices, non-volatile memory devices, and M/NEMS technology for ultra-low power circuits.  She is probably best known for the development of polycrystalline silicon-germanium thin film technology for applications in integrated circuits and microsystems; and as the co-inventor of the three-dimensional FinFET transistor  which is the design that is used in all leading microprocessor chips today.

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.

EECS alumnus Yang You (Ph.D. '20, advisor: James Demmel) has won the IEEE Computer Society Technical Consortium on High Performance Computing (TCHPC) Early Career Researcher Award for Excellence in High Performance Computing.  The focus of his research is efficient deep learning on distributed systems. He is known for developing the industry benchmark LARS (Layer-wise Adaptive Rate Scaling) and LAMB (Layer-wise Adaptive Moments for Batch training) optimizers to accelerate machine learning on HPC platforms.  His team broke the world record of ImageNet training speed in 2017 and the world record of BERT training speed in 2019, and his training techniques have been used by many tech giants like Google, Microsoft, and NVIDIA.  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.

Sumit Gulwani (Ph.D. '05, advisor: George Necula), now a Partner Research Manager at Microsoft Research in Redmond, Washington, has been selected to receive the 2021 Max Planck-Humboldt Medal for "automatic programming and computational education."  Gulwani, who won the ACM SIGPLAN Doctoral Dissertation award and the MSR Ph.d. Fellowship while at Berkeley, is an expert in program analysis and artificial intelligence.  He shaped the field of program synthesis, which emerged around 2010, by developing algorithms that can efficiently generate computer programs from very few input-output examples, natural-language-based specification, or from just the code and data context. His work made it possible for non-programmers to program tedious, repetitive spreadsheet tasks, and enabled productivity improvements for data scientists and developers for data wrangling and software engineering tasks. Recently, Gulwani has also been using the tools of program synthesis for computer-aided education of pupils and students. Starting from the automatic correction of learners' work in programming education, he further evolved this line of work to detect misunderstandings and give learning feedback and grades, also in subjects like mathematics and language learning. He is also the inventor of the popular Flash Fill feature in Microsoft Excel.  The award will be presented during a ceremony in Berlin on November 3, 2022.

CS Prof. Katherine Yelick has been named UC Berkeley's next vice chancellor for research.  She will take over the role from EECS Prof. Randy Katz on January 1, 2022.  Yelick is an expert in the field of parallel computing and currently serves as executive associate dean in the Division of Computing, Data Science, and Society (CDSS).  “Kathy Yelick is one of the most talented leaders I have ever worked with — she listens, sees the big picture, and co-creates and implements phenomenal solutions,” said Jennifer Chayes, the CDSS Associate Provost. “I cannot imagine a better vice chancellor for research, and we at CDSS look forward to working with Kathy in her new role.” Yelick spent 11 years in leadership and management roles at Berkeley Lab (LBNL), where she oversaw a variety of initiatives, including the opening of new computing facility Shyh Wang Hall, the founding of the Berkeley Quantum collaboration, the formation of the lab’s machine learning for science initiative, and the launch of the U.S. Department of Energy’s Exascale Computing Project.  “UC Berkeley’s research community is uniquely positioned to tackle some of the world’s most important social and scientific problems, from climate change and public health to equity and social justice,” Yelick said. “I think it’s important to bring together diverse expertise and perspectives, and I look forward to collaborating with my colleagues across academic disciplines, from the humanities and social sciences to the physical and biological sciences, engineering, professional schools and beyond.”

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."

EECS Assistant Prof. Gopala Anumanchipalli has been selected for the Rose Hills Innovator Program which supports distinguished early-career UC Berkley faculty who are "interested in developing highly innovative research programs" in STEM fields.  The program will provide discretionary research support of up to $85,000 per year for "projects with an exceptionally high scientific promise that may generate significant follow-on funding."   Anumanchipalli's project, titled "Multimodal Intelligent Interfaces for Assistive Communication," proposes to "improve the current state of assistive communication technologies by integrating multiple neural and behavioral sensing modalities, and tightly integrating the graphical interfaces, and personalizing them to the user’s context."  His team will use "state-of-the-art neural engineering and artificial intelligence to develop novel communication interfaces" including Electrocorticography, non-invsive in-ear Electroencephalography sensors and functional near infrared spectroscopy.  They will also use on-device speech recognition and dialog management to incorporate the acoustic context of the user.

EECS Prof. Sanjit Seshia was a recipient of the CAV Award at the 2021 International Conference on Computer-Aided Verification (CAV) earlier this month.  This award is presented annually "for fundamental contributions to the field of Computer-Aided Verification," and comes with a cash prize of $10K that is shared equally among recipients.  This year's award specifically recognizes “pioneering contributions to the foundations of the theory and practice of satisfiability modulo theories (SMT).”  Seshia's Ph.D. thesis work on the UCLID verifier and decision procedure helped lay the groundwork for this field.  SMT solvers are critical to verification of software and hardware model checking, symbolic execution, program verification, compiler verification, verifying cyber-physical systems, and program synthesis. Other applications include planning, biological modeling, database integrity, network security, scheduling, and automatic exploit generation.  CAV is the premier international conference on computer-aided verification and  provides a forum for a broad range of advanced research in areas ranging from model checking and automated theorem proving to testing, synthesis and related fields.

"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.