School of Engineering
Showing 201-250 of 449 Results
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Joseph Li
Graduate, Stanford Center for Professional Development
BioLearner and thinker in Artificial Intelligence, pushing the boundary of technology innovation for the good of the society.
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Wei Li
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioFrom his Cornell supercomputing PhD to nearly three decades at Intel—the last decade as VP/GM of AI & Analytics—Dr. Wei Li is a Stanford Adjunct Professor partnering with researchers, founders, VCs, and boards to bridge AI innovation with enterprise-scale impact.
Current Academic & Clinical Focus: As an Adjunct Professor at the Institute for Computational and Mathematical Engineering (ICME) and Affiliate Faculty at the Center for Artificial Intelligence in Medicine and Imaging (AIMI), Dr. Li specializes in AI strategy, enterprise governance, and commercial scale. His work centers on Innovation to Impact (I2I) and Trusted AI—bridging the gap between frontier technical research, clinical adoption, and real-world deployment. He collaborates across Stanford Engineering, Medicine, and Stanford Health Care for AI deployment in high-stakes environments.
Enterprise & Open Source Leadership: Prior to Stanford, Dr. Li spent nearly three decades at Intel Corporation, serving as Vice President and General Manager of AI & Analytics. In this role, he led global teams across 10+ countries building full-stack AI software platforms and hardware-software co-design that powered multi-billion-dollar product revenues. A long-time advocate for open science and industry oversight, he previously served on the governing boards of the PyTorch Foundation and Linux Foundation AI & Data alongside leaders from Meta, Google, OpenAI, Hugging Face, and Microsoft.
Scholarship & Academic Background: Dr. Li holds a Ph.D. in Computer Science from Cornell University in supercomputing research and completed executive education at the Stanford Graduate School of Business. He is a recipient of the ACM ASPLOS Best Paper Award, a former Associate Editor for ACM TOPLAS, and served as the Intel Executive Sponsor for Cornell University while sitting on the funding committee overseeing $20M in parallel computing research at UC Berkeley and UIUC.
Keynotes & Media Contributions: A prominent voice on AI strategy, enterprise deployment, and governance, Dr. Li is a frequent keynote speaker at major global forums—including CES, the World AI Summit, GITEX, and Harvard Business School. He also regularly contributes expert commentary to leading business and technology outlets, including Bloomberg, Forbes, and Fortune. -
Zewen (Evan) Li
Graduate, Stanford Center for Professional Development
BioZewen (Evan) Li, Deep Learning Engineer @NVIDIA (Santa Clara) & Online Grad student @Stanford, received M.S. degree from Carnegie Mellon University, B.E. degree from Computer Science and Technology of Hohai University.
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Jing Liang
Postdoctoral Scholar, Computer Science
BioJing Liang is a postdoctoral scholar in the Department of Computer Science at Stanford University, where he is affiliated with the Stanford Robotics Center and the Stanford Center on Longevity. He received his Ph.D. in Computer Science from the University of Maryland, College Park.
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Percy Liang
Professor of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
