CS alumni Xiaoye Sherry Li (Ph.D. '96, advisor: James Demmel) and Richard Vuduc (Ph.D. '03, advisor: James Demmel) have, along with Piyush Sao of Georgia Tech, won the 2022 Society for Industrial and Applied Mathematics (SIAM) Activity Group on Supercomputing (AG/SC) Best Paper Prize.  This prize recognizes "the author or authors of the most outstanding paper in the field of parallel scientific and engineering computing published in English in a peer-reviewed journal." Their paper, "A communication-avoiding 3D algorithm for sparse LU factorization on heterogeneous systems,” was published in 2018 in the IEEE International Parallel and Distributed Processing Symposium (IPDPS).  Li is now a Senior Scientist at Lawrence Berkeley National Laboratory (LBNL) where she works on diverse problems in high performance scientific computations, including parallel computing, sparse matrix computations, high precision arithmetic, and combinatorial scientific computing.  Vuduc, now an Associate Professor in the School of Computational Science and Engineering at Georgia Tech, is interested in high-performance computing, with an emphasis on algorithms, performance analysis, and performance engineering.

CS alumna Medha Kothari (B.A. '20) is featured in an episode of California magazine's The Edge podcast titled "Blockchain for the People."  While still a student, Kothari, who is currently a Research Partner at Variant, founded she256, a non-profit that "aims to increase diversity and break down barriers to entry in the blockchain space."  She discusses what blockchain is and why it has the potential to be a fairer technology "that can change the world."  Produced by the Cal Alumni Association, The Edge podcast series explores "cutting-edge ideas in science, tech, and society coming out of UC Berkeley."

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.

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.”

The UC Berkeley Black Engineering and Science Alumni Club (BESAC) has been selected by the Cal Alumni Association Board of Directors and the UC Berkeley Foundation Board of Trustees to receive the 2021 Loyal Company Outstanding Volunteer Group Award. This award "commends a volunteer group or alumni chapter that has maintained a meaningful relationship to Berkeley while successfully engaging its members through events, programs, and philanthropic opportunities." BESAC's mission "is to improve the opportunities and support for Cal Black alumni, students, professors, and staff in engineering and sciences and to bring UC Berkeley alumni together in organized efforts to benefit the members of the chapter and UC Berkeley."  The award will be presented during Reunion and Parents Weekend, on October 1st.

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.

EECS alumna and current Master's student Gloria Tumushabe (B.S. ’20) is the subject of an article in the Spring 2021 Berkeley Engineer titled "Cultivating female coders in Africa."  During the COVID pandemic shutdown, Tumushabe developed a program called Afro Fem Coders to allow her to remotely teach computer programming to girls in Uganda from her home in Walnut Creek.  Two weeks after reaching out by word-of-mouth and social media, she had heard back from more than 40 girls who were eager to participate.  She sent them money to pay for laptops and internet service, and formed an international network of women professionals to provide one-on-one mentoring.  In the year since the program began, it has grown to 120 girls from Uganda, Kenya, Tanzania, Namibia, Botswana and Ethiopia. “The more of us women in this space, the better,” she said.  Tumushabe is leading the EECS Anti-Racism Committee meetings this semester, and was awarded the 2021 EECS Eugene L. Lawler Prize for her "amazing work and dedication to diversity, equity and inclusion, and improving the EECS Department for students who come after her."

EECS alumnus Yang You (Ph.D. '20, advisor: James Demmel) has been named in the Forbes 30 Under 30 2021 Asia list for Healthcare and Science.  Yang, who is now a Presidential Young Professor of Computer Science at the National University of Singapore, studies Machine Learning, Parallel/Distributed Algorithms, and High-Performance Computing. The focus of his research is scaling up deep neural networks training on distributed systems or supercomputers.  He has broken two world records for AI training speed: one in 2017 for ImageNet and the other in 2019 for Boundless Electrical Resistivity Tomography (BERT).  Yang has won numerous best paper awards as well as the inaugural Berkeley EECS Lotfi A. Zadeh Prize for outstanding contributions to soft computing and its applications by a graduate student.