School of Engineering
Showing 1,801-1,900 of 2,153 Results
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Brian Trippe
Assistant Professor of Statistics and, by courtesy, of Computer Science
BioDr. Brian Trippe is an assistant professor at Stanford in the Department of Statistics, with an affiliation in Stanford Data Science.
In his research, Dr. Trippe develops probabilistic machine learning methods to address challenges in biotechnology and medicine. Recently, his focus has been on generative modeling and inference algorithms for protein engineering.
Before joining Stanford, Dr. Trippe was a postdoctoral fellow at Columbia University in the Department of Statistics, and a visiting researcher at the Institute for Protein Design at the University of Washington. -
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, 2024 and 2025 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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Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering and, by courtesy, of Computer Science
BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department's Graduate Teaching Award, and the Lanchester Prize. He was the plenary speaker at the 2019 Allerton Conference on Communications, Control, and Computing. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen. -
Dakuo Wang
Visiting Associate Professor, Computer Science
BioDakuo Wang is a Visiting Associate Professor at Stanford University, and an Associate Professor at Northeastern University, jointly appointed at Khoury College of Computer Sciences and the College of Arts, Media and Design. At Northeastern, Dakuo Wang leads the Northeastern University Human-Centered AI Lab (NEU HAI), and he is also the Founding Director of the AI Application Graduate Program. His research lies at the intersection of human-computer interaction (HCI) and artificial intelligence (AI), with a focus on the exploration, development, and evaluation of human-centered AI (HCAI) systems to achieve human-AI collaboration.
Before joining Northeastern, Dakuo Wang was a Senior Staff Member at IBM Research, Principal Investigator at MIT-IBM Watson AI Lab, and a Visiting Scholar at Stanford Institute for Human-Centered Artificial Intelligence (Stanford HAI). He got his Ph.D. from the University of California Irvine (advisor: Judith Olson and Gary Olson). He has worked as a designer, researcher, and engineer in the U.S., China, and France. He serves in organizing committees, program committees, and editorial boards for a variety of venues, and ACM has recognized him as an ACM Distinguished Speaker.
