School of Engineering
Showing 2,901-3,000 of 5,910 Results
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Fei-Fei Li
Sequoia Capital Professor, Senior Fellow at HAI and Professor, by courtesy, of Operations, Information and Technology at the Graduate School of Business
Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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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)
BioSummary:
After starting in supercomputing research for my PhD at Cornell and then spending nearly three decades at Intel—the last decade as the VP/GM of AI & Analytics—I returned to the research and startup ecosystem. Today, I am helping AI founders, Stanford students, and corporate boards bridge the gap between AI innovation and real-world impact.
Current Academic & Clinical Focus:
As an Adjunct Professor in the School of Engineering and Affiliate Faculty at the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), I specialize in AI strategy, enterprise governance, and commercial scale. My work centers on Innovation to Impact (I2I) and Trusted AI—bridging the gap between frontier technical research, clinical adoption, and real-world deployment. I collaborate across the School of Engineering, the School of Medicine, and Stanford Health Care as a strategic architect and educator for AI deployment in high-stakes environments.
Enterprise & Open Source Leadership:
Prior to Stanford, I spent nearly three decades at Intel Corporation, serving as Vice President and General Manager of AI & Analytics. In this role, I led global engineering teams across 10+ countries building full-stack AI software platforms powering enterprise-scale infrastructure. A long-time advocate for open science and industry oversight, I 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:
I hold a Ph.D. in Computer Science from Cornell University in supercomputing research and completed executive education at the Stanford Graduate School of Business. I am 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, I am a frequent keynote speaker at major global forums—including CES, the World AI Summit, GITEX, and Harvard Business School. I also regularly contribute expert commentary to leading business and technology outlets, including Bloomberg, Forbes, and Fortune. -
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.
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Kang Rui Garrick Lim
Postdoctoral Scholar, Chemical Engineering
BioI am a materials chemist from Singapore and presently, a Stanford Energy Postdoctoral Fellow with Prof. Matteo Cargnello and Prof. Thomas F. Jaramillo at Stanford University. In 2027, I will start as a Nanyang Assistant Professor at the School of Materials Science & Engineering in Nanyang Technological University (NTU), Singapore. I completed my PhD and Master's degree in chemistry at Harvard University under Prof. Joanna Aizenberg, and my Bachelor's degree in chemistry from the National University of Singapore (NUS).
At Stanford and SLAC National Accelerator Laboratory (2025-), I work on colloidal catalyst design for CO2 conversion as part of the SUNCAT Center for Interface Science and Catalysis. During my PhD at Harvard (2020-2025), I integrated colloidal templating and self-assembly concepts into catalyst design to design 3D macroporous inverse opal structures bearing partially embedded dilute alloy nanoparticles to serve as a model thermocatalytic platform. Previously, at NUS and IMRE A*STAR in Singapore (2018-2020), I synthesized MXene nanohybrids for electrocatalysis and designed core-shell quantum dots for light harvesting. My broader research interest is to leverage on colloidal design of catalytic architectures–their active sites and immediate environment–to bridge the materials gap in catalyst design for low carbon energy research. -
Michael Lin
Professor of Neurobiology, of Bioengineering and, by courtesy, of Chemical and Systems Biology
Current Research and Scholarly InterestsOur lab applies biochemical and engineering principles to the development of protein-based tools for investigating biology in living animals. Topics of investigation include fluorescent protein-based voltage indicators, synthetic light-controllable proteins, bioluminescent reporters, and applications to studying animal models of disease.
