EECS alumnus Warren “Woody” Hoburg (M.S. '11/Ph.D. '13, advisor: Pieter Abbeel), one of the first graduates of NASA's Artemis astronaut basic training program in 2020, has been assigned to launch on the agency’s SpaceX Crew-6 mission – the sixth crew rotation flight aboard a Crew Dragon spacecraft to the International Space Station.  Hoburg will pilot the spacecraft when it is expected to launch from a Falcon 9 rocket at NASA's Kennedy Space Center in 2023.  This will be his first mission into space.  At the time of his selection as an astronaut, Hoburg was a commercial pilot and an assistant professor of aeronautics and astronautics at MIT.  His research focused on efficient methods for design of engineering systems.

2003 Distinguished CS Alumnus Madhu Sudan (Ph.D. '92, advisor: Umesh Vazirani) has won the Institute of Electrical and Electronics Engineers (IEEE) Hamming Medal.  This award recognizes "exceptional contributions to information sciences, systems, and technology."   Sudan was cited “for fundamental contributions to probabilistically checkable proofs and list decoding of Reed-Solomon codes.”  He won the Berkeley EECS Sakrison Memorial Award for his graduate thesis, worked as a researcher at both the IBM Watson Research Center and Microsoft Research, was a professor of EECS and the Associate Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, and is now a professor at the Harvard School of Engineering and Applied Sciences (SEAS).  Sudan is known for his contributions to theoretical computer science, particularly for advancing the theory of probabilistically checkable proofs, which is a way to recast a mathematical proof in computer language for additional checks on its validity, and for developing error-correcting codes.

2008 Distinguished CS Alumna Deborah Estrin (B.S. EECS '80) has won the prestigious Institute of Electrical and Electronics Engineers (IEEE) John von Neumann Medal.  The award recognizes “outstanding achievements in computer-related science and technology.”  Estrin, whose research interests include technologies for caregiving, immersive health, small data, participatory sensing and public interest technology, was cited for “her leadership in mobile and wireless sensing systems technologies and applications, including personal health management.”  Now a professor at Cornell, Estrin was the founding director of the National Science Foundation Center for Embedded Networked Sensing (CENS) at UCLA, where she pioneered the development of mobile and wireless systems to collect and analyze real-time data about the physical world. She also co-founded the nonprofit startup Open mHealth, which creates open data sharing standards and tools that allow developers of health applications to store, process, and visualize data.

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.”

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.