School of Engineering
Showing 2,201-2,300 of 2,448 Results
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Gordon Wetzstein
Associate Professor of Electrical Engineering and, by courtesy, of Computer Science
BioGordon Wetzstein is an Associate Professor of Electrical Engineering and, by courtesy, of Computer Science at Stanford University. He is the leader of the Stanford Computational Imaging Lab and a faculty co-director of the Stanford Center for Image Systems Engineering. At the intersection of computer graphics and vision, artificial intelligence, computational optics, and applied vision science, Prof. Wetzstein's research has a wide range of applications in next-generation imaging, wearable computing, and neural rendering systems. Prof. Wetzstein is a Fellow of Optica and the recipient of numerous awards, including an NSF CAREER Award, an Alfred P. Sloan Fellowship, an ACM SIGGRAPH Significant New Researcher Award, a Presidential Early Career Award for Scientists and Engineers (PECASE), an SPIE Early Career Achievement Award, an Electronic Imaging Scientist of the Year Award, an Alain Fournier Ph.D. Dissertation Award as well as many Best Paper and Demo Awards.
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Jennifer Widom
Frederick Emmons Terman Dean of the School of Engineering, Fletcher Jones Professor of Computer Science and Professor of Electrical Engineering
BioJennifer Widom is the Frederick Emmons Terman Dean of the School of Engineering and the Fletcher Jones Professor in Computer Science and Electrical Engineering at Stanford University. She served as Computer Science Department Chair from 2009-2014 and School of Engineering Senior Associate Dean from 2014-2016. Jennifer received her Bachelor's degree from the Indiana University Jacobs School of Music in 1982 and her Computer Science Ph.D. from Cornell University in 1987. She was a Research Staff Member at the IBM Almaden Research Center before joining the Stanford faculty in 1993. Her research interests span many aspects of nontraditional data management. She is an ACM Fellow and a member of the National Academy of Engineering and the American Academy of Arts & Sciences; she received a Guggenheim Fellowship in 2000, the ACM SIGMOD Edgar F. Codd Innovations Award in 2007, the ACM-W Athena Lecturer Award in 2015, and the EPFL-WISH Foundation Erna Hamburger Prize in 2018.
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Terry Winograd
Professor of Computer Science, Emeritus
BioProfessor Winograd's focus is on human-computer interaction design and the design of technologies for development. He directs the teaching programs and HCI research in the Stanford Human-Computer Interaction Group, which recently celebrated it's 20th anniversary. He is also a founding faculty member of the Hasso Plattner Institute of Design at Stanford (the "d.school") and on the faculty of the Center on Democracy, Development, and the Rule of Law (CDDRL)
Winograd was a founding member and past president of Computer Professionals for Social Responsibility. He is on a number of journal editorial boards, including Human Computer Interaction, ACM Transactions on Computer Human Interaction, and Informatica. He has advised a number of companies started by his students, including Google. In 2011 he received the ACM SIGCHI Lifetime Research Award. -
Keith Winstein
Associate Professor of Computer Science and, by courtesy, of Electrical Engineering
BioKeith Winstein is an associate professor of computer science and, by courtesy, of electrical engineering at Stanford University. His research group creates new kinds of networked systems by rethinking abstractions around communication, compression, and computing. Some of his group’s research has found broader use, including the Mosh tool, the Puffer video-streaming site, the Lepton compression tool, the Mahimahi network emulators, and the gg lambda-computing framework. He has received the SIGCOMM Rising Star Award, the Sloan Research Fellowship, the NSF CAREER Award, the Usenix NSDI Community Award (2020, 2017), the Usenix ATC Best Paper Award, the Applied Networking Research Prize, the SIGCOMM Doctoral Dissertation Award, and a Sprowls award for best doctoral thesis in computer science at MIT. Winstein previously served as a staff reporter at The Wall Street Journal and worked at Ksplice, a startup company (now part of Oracle) where he was the vice president of product management and business development and also cleaned the bathroom. He did his undergraduate and graduate work at MIT.
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Christina R Wodtke
Lecturer
BioChristina Wodtke is an author, speaker, and lecturer at Stanford with insight into human innovation and high-performing teams. Her resume includes re-design and initial product offerings with LinkedIn, MySpace, Zynga, Yahoo! and others, as well as founding three startups, an online design magazine called Boxes and Arrows, and co-founding the Information Architecture Institute.
Christina uses the power of story to connect with audiences and readers through her worldwide speaking engagements and her Amazon category-bestselling books. Her bestselling book, Radical Focus, tackles the OKR movement and startup culture with an eye to getting the right things done. Her other books include The Team that Managed Itself, Information Architecture: Blueprints for the Web and Pencil Me In (on visual thinking for the workplace.) Christina’s work is personable, insightful, knowledgeable, and engaging. Find out more information (and get your Focus worksheet) at cwodtke.com. -
Michael Wornow
Ph.D. Student in Computer Science, admitted Autumn 2020
BioMichael is a computer science PhD student focused on developing and operationalizing large-scale pretrained models ("foundation models") in healthcare. He is advised by Nigam Shah and Chris Re and is supported by an NSF Graduate Research Fellowship.
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Jiajun Wu
Assistant Professor of Computer Science and, by courtesy, of Psychology
BioJiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from J.P. Morgan, Samsung, Amazon, and Meta.
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Min Wu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsAI safety: robustness and explainability. Automated verification.
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Tiange Xiang
Ph.D. Student in Computer Science, admitted Autumn 2022
Masters Student in Computer Science, admitted Spring 2024BioTiange Xiang is a Ph.D. student in Computer Science at Stanford University, where he is a member of the Stanford AI Lab (SAIL) and Stanford Vision and Learning Lab (SVL). His research interests include machine learning and computer vision in general. He received a bachelor's degree in Computer Science and Technology (Advanced)(Honors) from the University of Sydney, where he was awarded Honors Class I and the University Medal.
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Alana Xiang
Undergraduate, Computer Science
BioMy goal is to make the future amazing.
I'm currently focused on studying the alignment of AI systems.
I have spent time at MATS, METR, CLR, and Meta. -
Pei Xu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly Interestscharacter animation, physics-based character control, crowd simulation
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Daniel Yamins
Assistant Professor of Psychology and of Computer Science
Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:
H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.
H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.
We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis.
