School of Engineering
Showing 101-133 of 133 Results
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Yoav Shoham
Professor of Computer Science, Emeritus
BioYoav Shoham is professor emeritus of computer science at Stanford University. A leading AI expert, Prof. Shoham is Fellow of AAAI, ACM and the Game Theory Society. Among his awards are the IJCAI Research Excellence Award, the AAAI/ACM Allen Newell Award, and the ACM/SIGAI Autonomous Agents Research Award. His online Game Theory course has been watched by close to a million people. Prof. Shoham has founded several AI companies, including TradingDynamics (acquired by Ariba), Katango and Timeful (both acquired by Google), and AI21 Labs. Prof. Shoham also chairs the AI Index initiative (www.AIindex.org), which tracks global AI activity and progress, and WeCode (www.wecode.org.il), a nonprofit initiative to train high-quality programmers from disadvantaged populations.
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Aaron Sidford
Associate Professor of Management Science and Engineering and of Computer Science
Current Research and Scholarly InterestsMy research interests lie broadly in the optimization, the theory of computation, and the design and analysis of algorithms. I am particularly interested in work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures.
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Shuran Song
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioShuran Song is an Assistant Professor of Electrical Engineering at Stanford University. Before joining Stanford, she was faculty at Columbia University. Shuran received her Ph.D. in Computer Science at Princeton University, BEng. at HKUST. Her research interests lie at the intersection of computer vision and robotics. Song’s research has been recognized through several awards, including the Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21, RSS’19, and finalists at RSS, ICRA, CVPR, and IROS. She is also a recipient of the NSF Career Award, Sloan Foundation fellowship as well as research awards from Microsoft, Toyota Research, Google, Amazon, and JP Morgan.
To learn more about Shuran’s work, please visit: https://shurans.github.io/ -
Hariharan Subramonyam
Assistant Professor (Research) of Education and, by courtesy, of Computer Science
BioHari Subramonyam is an Assistant Professor (Research) at the Graduate School of Education and a Faculty Fellow at Stanford's Institute for Human-Centered AI. He is also a member of the HCI Group at Stanford. His research focuses on augmenting critical human tasks (such as learning, creativity, and sensemaking) with AI by incorporating principles from cognitive psychology. He also investigates support tools for multidisciplinary teams to co-design AI experiences. His work has received multiple best paper awards at top human-computer interaction conferences, including CHI and IUI.
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Li-Yang Tan
Assistant Professor of Computer Science
Current Research and Scholarly InterestsTheoretical computer science, with an emphasis on complexity theory
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Caroline Trippel
Assistant Professor of Computer Science and of Electrical Engineering
BioCaroline Trippel is an Assistant Professor in the Computer Science and Electrical Engineering Departments at Stanford University working in the area of computer architecture. Prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Her work focuses on promoting correctness and security as first-order computer systems design metrics (akin to performance and power). A central theme of her work is leveraging formal methods techniques to design and verify hardware systems in order to ensure that they can provide correctness and security guarantees for the applications they intend to support. Additionally, Trippel has been recently exploring the role of architecture in enabling privacy-preserving machine learning, the role of machine learning in hardware systems optimizations, particularly in the context of neural recommendation, and opportunities for improving datacenter and at-scale machine learning reliability.
Trippel's research has influenced the design of the RISC-V ISA memory consistency model both via her formal analysis of its draft specification and her subsequent participation in the RISC-V Memory Model Task Group. Additionally, her work produced a novel methodology and tool that synthesized two new variants of the now-famous Meltdown and Spectre attacks.
Trippel's research has been recognized with IEEE Top Picks distinctions, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, and the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering. She was also awarded an NVIDIA Graduate Fellowship (2017-2018) and selected to attend the 2018 MIT Rising Stars in EECS Workshop. Trippel completed her PhD in Computer Science at Princeton University and her BS in Computer Engineering at Purdue University. -
Nick Troccoli
Lecturer
BioNick Troccoli is a Lecturer in the Stanford Computer Science Department. He started as a full-time lecturer at Stanford in Fall 2018, after graduating from Stanford in June 2018 with Bachelor's and Master's Degrees in Computer Science. He has taught CS106X, CS107, CS110 and CS111. In 2022, he was named to the Tau Beta Pi Teaching Honor Roll. During his undergraduate career, he specialized in Systems, and during his graduate career he specialized in Artificial Intelligence. He was heavily involved in teaching as both an undergraduate and graduate student; he was an undergraduate Section Leader in the CS 198 Section Leading Program, a graduate CA (Course Assistant) for CS 181, the Head TA for CS 106A and CS 106B, and the summer 2017 instructor for CS 106A. In 2017 he was awarded the Forsythe Teaching Award and the Centennial TA Award for excellence in teaching.
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Jeffrey Ullman
Stanford Warren Ascherman Professor of Engineering , Emeritus
BioJeff Ullman is the Stanford W. Ascherman Professor of Engineering
(Emeritus) in the Department of Computer Science at Stanford and CEO
of Gradiance Corp. He received the B.S. degree from Columbia
University in 1963 and the PhD from Princeton in 1966. Prior to his
appointment at Stanford in 1979, he was a member of the technical
staff of Bell Laboratories from
1966-1969, and on the faculty of Princeton University between
1969 and 1979. From 1990-1994, he was chair of the Stanford Computer
Science Department. Ullman was elected to the National Academy of
Engineering in 1989, the American Academy of Arts and Sciences in
2012, and has held Guggenheim and Einstein Fellowships. He has
received the Sigmod Contributions Award (1996), the ACM Karl V. Karlstrom
Outstanding Educator Award (1998), the Knuth Prize (2000),
the Sigmod E. F. Codd Innovations award (2006), the IEEE von
Neumann medal (2010), and the NEC C&C Foundation Prize (2017).
He is the author of 16 books, including books
on database systems, compilers, automata theory, and algorithms. -
Camille Utterback
Associate Professor of Art and Art History and, by courtesy, of Computer Science
BioCamille Utterback is an internationally acclaimed artist whose interactive installations and reactive sculptures engage participants in a dynamic process of kinesthetic discovery and play. Utterback’s work explores the aesthetic and experiential possibilities of linking computational systems to human movement and gesture in layered and often humorous ways. Her work focuses attention on the continued relevance and richness of the body in our increasingly mediated world.
Her work has been exhibited at galleries, festivals, and museums internationally, including The Frist Center for Visual Arts, Nashville, TN; The Orange County Museum of Art, Newport Beach, CA; ZERO1 The Art & Technology Network, San Jose, CA; The New Museum of Contemporary Art, The American Museum of the Moving Image, New York; The NTT InterCommunication Center, Tokyo; The Seoul Metropolitan Museum of Art; The Netherlands Institute for Media Art; The Taipei Museum of Contemporary Art; The Center for Contemporary Art, Kiev, Ukraine; and the Ars Electronica Center, Austria. Utterback’s work is in private and public collections including Hewlett Packard, Itaú Cultural Institute in São Paolo, Brazil, and La Caixa Foundation in Barcelona, Spain.
Awards and honors include a MacArthur Foundation Fellowship (2009), a Transmediale International Media Art Festival Award (2005), a Rockefeller Foundation New Media Fellowship (2002) and a commission from the Whitney Museum for the CODeDOC project on their ArtPort website (2002). Utterback holds a US patent for a video tracking system she developed while working as a research fellow at New York University (2004). Her work has been featured in The New York Times (2010, 2009, 2003, 2002, 2001), Art in America (October, 2004), Wired Magazine (February 2004), ARTnews (2001) and many other publications. It is also included in Thames & Hudson’s World of Art – Digital Art book (2003) by Christiane Paul.
Recent public commissions include works for the Liberty Mutual Group, the FOR-SITE Foundation, The Sacramento Airport, The City of San Jose, California, The City of Fontana, California, and the City of St. Louis Park, Minnesota. Other commissions include projects for The American Museum of Natural History in New York, The Pittsburgh Children’s Museum, The Manhattan Children’s Museum, Herman Miller, Shiseido Cosmetics, and other private corporations.
Utterback is currently an Assistant Professor in the Art and Art History Department at Stanford University. She holds a BA in Art from Williams College, and a Masters degree from The Interactive Telecommunications Program at New York University’s Tisch School of the Arts. She currently lives and works in San Francisco. -
Gregory Valiant
Associate Professor of Computer Science
Current Research and Scholarly InterestsMy primary research interests lie at the intersection of algorithms, learning, applied probability, and statistics. I am particularly interested in understanding the algorithmic and information theoretic possibilities and limitations for many fundamental information extraction tasks that underly real-world machine learning and data-centric applications.
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Ge Wang
Associate Professor of Music, Senior Fellow at the Stanford Institute for HAI and Associate Professor, by courtesy, of Computer Science
BioGe Wang is an Associate Professor at Stanford University in the Center for Computer Research in Music and Acoustics (CCRMA). He specializes in the art of design and computer music — researching programming languages and interactive software design for music, interaction design, mobile music, laptop orchestras, expressive design of virtual reality, aesthetics of music technology design, and education at the intersection of computer science and music. Ge is the author of the ChucK music programming language, the founding director of the Stanford Laptop Orchestra (SLOrk). Ge is also the Co-founder of Smule (reaching over 200 million users), and the designer of the iPhone's Ocarina and Magic Piano. Ge is a 2016 Guggenheim Fellow, and the author of ARTFUL DESIGN: TECHNOLOGY IN SEARCH OF THE SUBLIME—a book on design and technology, art and life‚ published by Stanford University Press in 2018 (see https://artful.design/)
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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. -
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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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. -
Diyi Yang
Assistant Professor of Computer Science
BioDiyi Yang is an Assistant Professor in Computer Science at Stanford University. Professor Yang's research interests are Computational Social Science and Natural Language Processing. Her research goal is to understand the social aspects of language and then build socially aware NLP systems to better support human-human and human-computer interaction. Professor Yang received her PhD from the School of Computer Science, Carnegie Mellon University, and her bachelor's degree from Shanghai Jiao Tong University, China. Her work has received multiple best paper nominations or awards at ICWSM, EMNLP, SIGCHI, ACL, and CSCW. She is a recipient of Forbes 30 under 30 in Science, IEEE “AI 10 to Watch”, the Intel Rising Star Faculty Award, Microsoft Research Faculty Fellowship, and NSF CAREER Award.
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Serena Yeung
Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering
BioDr. Serena Yeung is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.
Dr. Yeung leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, the Center for Artificial Intelligence in Medicine & Imaging, the Center for Human-Centered Artificial Intelligence, and Bio-X. She also serves on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence. -
James Zou
Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy group works on both foundations of statistical machine learning and applications in biomedicine and healthcare. We develop new technologies that make ML more accountable to humans, more reliable/robust and reveals core scientific insights.
We want our ML to be impactful and beneficial, and as such, we are deeply motivated by transformative applications in biotech and health. We collaborate with and advise many academic and industry groups.
