School of Engineering
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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.
