School of Engineering
Showing 401-410 of 1,781 Results
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Judith Ellen Fan
Assistant Professor of Psychology, by courtesy, of Education and of Computer Science
BioI direct the Cognitive Tools Lab (https://cogtoolslab.github.io/) at Stanford University. Our lab aims to reverse engineer the human cognitive toolkit—in particular, how people use physical representations of thought to learn, communicate, and solve problems. Toward this end, we use a combination of approaches from cognitive science, computational neuroscience, and artificial intelligence to achieve deeper understanding of quintessentially human ways of thinking and imagining. Our broader goal is to leverage such scientific understanding of human cognition to guide the development of technologies that augment human agency and creativity.
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Haoquan Fang
Ph.D. Student in Computer Science, admitted Autumn 2026
BioHaoquan is a CS PhD student at Stanford University, advised by Prof Fei-Fei Li as part of the Stanford Vision and Learning Lab. Currently, he is also a research intern at NVIDIA Cosmos Lab, working with VP Ming-Yu Liu and Dr Haotian Zhang.
Previously, he has spent time at Ai2 PRIOR and Ai2 Robotics. He obtained his BS degree from the University of Washington, where he double majored in computer science (with honors) and statistics, and minored in mathematics. He was advised by Prof Ranjay Krishna, Prof Ali Farhadi, Prof Dieter Fox, and Prof Jenq-Neng Hwang. He was also mentored by and collaborated with Prof Jiafei Duan and Dr Ying Jin.
His research interests lie broadly in robot learning. In particular, he focuses on developing foundation models for robotic manipulation that are deployable in the real world and unlock novel capabilities. -
Kayvon Fatahalian
Associate Professor of Computer Science
BioKayvon Fatahalian is an Associate Professor in the Computer Science Department at Stanford University. Kayvon's research focuses on the design of systems for real-time graphics, high-efficiency simulation engines for applications in entertainment and AI, and platforms for the analysis of images and videos at scale.
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Ron Fedkiw
Canon Professor in the School of Engineering
BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.
