Organizers

Andrew Howard: Senior Staff Software Engineer at Google Research, Andrew is working on efficient computer vision models for on device applications. He is the originator of Google’s popular MobileNet models.

Chas Leichner: Staff Software Engineer at Google Research, Chas is working on efficient computer vision models for mobile devices with an emphasis on increasing the usability of domain-specific accelerators. He has previously worked on neural network accelerator chip design for datacenter applications.

Peizhao Zhang: Research Scientist at Meta, Peizhao Zhang is a research scientist at Meta working on efficient deep learning. His work includes efficient model design, automatic architecture search, as well as efficient models for different applications. He holds a Ph.D. in Computer Science from Texas A&M University.

Bichen Wu: Research Scientist at Meta Bichen Wu is a research scientist at Meta working on efficient deep learning algorithms, models, and systems. His research includes efficient computer vision, 3D computer vision, neural architecture search, speech synthesis, and so on. He obtained his Ph.D. from UC Berkeley and his bachelor's degree from Tsinghua University.

Tao Xu: Research Scientist at Meta, Tao Xu is a research scientist at Meta since received her PhD degree in the Department of Computer Science and Engineering from Lehigh University in 2018. She received the BE degree in agricultural mechanization and automatization from China Agricultural University in 2010, and the MS degree in computer science from Chinese Academy of Science in 2013. Her current research interests include deep learning, computer vision, and generative networks.

Xiaoliang Dai: Research Scientist at Meta, Xiaoliang Dai is a research scientist working on the mobile vision team at Meta. His research interests lie in efficient deep neural networks, data-efficient learning, and related applications. He received the B.S. degree from Peking University in 2014, and the Ph.D. degree from Princeton University in 2019.

Kurt Keutzer: Professor at UC Berkeley Formerly Chief Technical Officer and Senior Vice-President of Research at Synopsys, since 1998 Kurt has been Professor of Electrical Engineering and Computer Science at the University of California at Berkeley. Kurt’s research group is currently focused on using highly-distributed parallelism to accelerate the training of Deep Neural Networks and on orchestrating a variety of techniques to produce fast energy-efficient nets for applications in embedded computer vision. Kurt has published six books, over 250 refereed articles, and is a Fellow of the IEEE. Kurt has been an invited speaker on the topic of Efficient Deep Learning in workshops at NIPS (2016, 2018), CVPR (2018) and ICML 2017 (represented by his student, Forrest Iandola). Kurt is on the steering committee of the TinyML workshop co-sponsored by Google and Qualcomm.

Peter Vajda: Research Scientist Manager at Meta Peter joined Meta in 2014 as a Research Scientist. Currently, he is managing the Mobile Vision team on efficient computer vision algorithms for mobile devices. Before joining Meta, he was Visiting Assistant Professor at Stanford University, Stanford, USA, working on personalized multimedia systems and mobile visual search.

Yung-Hsiang Lu: Professor at Purdue University Yung-Hsiang Lu is a professor of Electrical and Computer Engineering at Purdue University. He is a University Faculty Scholar of Purdue University. He is a fellow of the IEEE (Institute of Electrical and Electronics Engineers), distinguished scientist and distinguished speaker of the ACM (Association for Computing Machinery). Dr. Lu is the inaugural director of Purdue’s John Martinson Engineering Entrepreneurial Center. In 2019, he received the Outstanding VIP-Based Entrepreneur Award from the VIP (Vertically Integrated Projects) Consortium. His research areas include computer vision, embedded systems, cloud and mobile computing. He is an editor of the book "Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence" (2022 by Chapman and Hall/CRC, ISBN 9780367744700)

Kate Saenko: Associate Professor at Boston University Kate Saenko is an Associate Professor at the Department of Computer Science at Boston University, and the director of the Computer Vision and Learning Group and member of the IVC Group. She received her PhD from MIT. Previously, she was an Assistant Professor at the Department of Computer Science at UMass Lowell, a Postdoctoral Researcher at the International Computer Science Institute, a Visiting Scholar at UC Berkeley EECS and a Visiting Postdoctoral Fellow in the School of Engineering and Applied Science at Harvard University. Her research interests are in the broad area of Artificial Intelligence with a focus on Adaptive Machine Learning, Learning for Vision and Language Understanding, and Deep Learning.

Ping Hu: PhD Candidate at Boston University Ping is a PhD candidate from the IVC group at Boston University. He is working on fast computer vision models, data-efficient learning, and open-world perception.

Dilin Wang: Research Scientist at Meta Meta Dilin’s research interests are primarily in machine learning, with a focus on energy-efficient deep learning and AR/VR. He did his Ph.D. in CS at UT Austin, where he was advised by Qiang Liu.