University of California, Berkeley
Department of Electrical Engineering and Computer Sciences

	Professor Yi Ma   Electrical Engineering and Computer Sciences University of California, Berkeley Office:    EECS Department, 333C Cory Hall # 1770               University of California, Berkeley, CA 94720-1770, USA. Email:     yima@eecs.berkeley.edu Phone:   +1 (510) 664 4565 Other Affiliations Berkeley Artificial Intelligence Research (BAIR) Berkeley Center for Augmented Cognition (CRC) Berkeley FHL Vive Center for Enhanced Reality
Teaching Research Publications Presentations Students Services Biography Honors CV.pdf
Spring 2022 Courses: CS294: Geometry and Learning for 3D Vision (Course Piazza and a tentative Syllabus.pdf) EECS106B/206B: Robotic Manipulation and Interaction (co-teach with Shankar Sastry). Recent Releases: A New Manuscript: ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction, (with Youtube Video) A New Textbook: High-Dimensional Data Analysis with Low-Dimensional Models (or a mirror site for download in China). A New Course EECS208: Computational Principles for High-Dimensional Data Analysis (with a Course Website and Lecture Slides). New and Recent Events: Keynote Speech at the International School on Deep Learning (DeepLearn 2022), United Kingdom, postponed to January 2023. Keynote Speech at the 4th International Conference on Robotics and Computer Vision (ICRCV), Wuhan, China, September 25-27, 2022. Plenary Talk at the 2nd Global Summit and Expo on Robot Intelligence Technology and Applications (GSERITA), Barcelona, Spain, September 19-22, 2022. Keynote Speech at the Hong Kong Tech Forum on Grand Challenges in Data Science and Artificial Intelligence, Hong Kong, July 26-27, 2022. Visit and talk at Oxford University, July 11-18, 2022. Plenary Talk at the Chinese SIAM Conference on Big Data and AI (CSIAM-BDAI), China, July 8-10, 2022. Summer Course at TBSI on Computational Principles for High-Dimensional Data Analysis, June 27 - July 8, 2022. Visit and talk at MBZUAI, Abu Dhabi, June 20-25, 2022. Keynote Speech at the biennial Canadian Workshop on Information Theory (CWIT) 2022, Ottawa, Canada, June 5-8, 2022. Invited talk at CS Department Seminar, UC Davis, June 2, 2022. A Five-Day Short Course on Low-Dim Models for High-Dim Data ICASSP, Singapore, May 22-27, 2022. Plenary Talk at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Singapore, May 22-27, 2022. Invited Talk at Baidu Research, April 29, 2022. Invited Talk at Facebook/Meta AI Research (FAIR/MAIR), April 25, 2022. MSRA CVPR panel discussion, April 22, 2022. Invited Talk at University of Washington, Seattle, April 8, 2022. Invited Talk at Washington University at St. Louis, March 23, 2022. Talk at BAIR Visual Computing Workshop, Berkeley, March 21, 2022. Invited Talk, Department of Electrical and Computer Engineering, University of Michigan, March 17, 2022. Invited Talk, joint Semiautonomous Seminar and THEORINET Seminar, EECS Berkeley, March 4, 2022. Distinguished Colloquium, Department of Electrical and Computer Engineering, University of Maryland, Januarary 28, 2022. Recorded video on Closed-Loop Data Transcription via Minimaxing Rate Reduction (with Paper), Berkeley Neuroscience Redwood Center, December 2, 2021. Recorded video on ReduNet: Deep (Convolution) Networks from First Principles (with Paper ), at CMSA of Harvard University, April 16, 2021. Recorded video on Learning to Detect Geometric Structures from Images, CVPR 3D Scene Understanding Workshop, June 19, 2021. Recorded video of An Overview of Reinforcement Learning and Optimal Control (with Slides), February 17, 2021. Berkeley Assured Autonomy Seminar (TBD, Spring 2022). Berkeley Learning Theory Study Group (TBD, Spring 2022). Project Websites: Deep Networks from the Principle of Rate Reduction. Pursuit of Large-Scale 3D Structures and Geometry. UIUC/MSRA: Low-Rank Matrix Recovery via Convex Optimization (with Wright, Lin and Candes et. al.). UIUC: Face Recognition via Sparse Representation (with Wright, Ganesh, Yang, Zhou and Wagner et. al.). UIUC: Clustering and Classification via Lossy Compression (with Wright Yang, Mobahi, and Rao et. al.). UIUC: Generalized Principal Component Analysis (with Huang and Vidal).   ©2017 Yi Ma Last modified: Thu May 12 00:02:37 PDT 2022