Dr. Oren Etzioni was Chief Executive Officer at AI2 from its inception until Sept. 30th, 2022. He now serves as an advisor & board member for AI2, and a technical director of the AI2 Incbuator. He is Professor Emeritus, University of Washington as of October 2020 and a Venture Partner at the Madrona Venture Group since 2000. His awards include AAAI Fellow and Seattle’s Geek of the Year. He has founded several companies including Farecast (acquired by Microsoft). He has written over 200 technical papers, as well as commentary on AI for The New York Times, Wired, and Nature. He helped to pioneer meta-search, online comparison shopping, machine reading, and Open Information Extraction.
“Much have I learned from my teachers, more from my colleagues, but from my students, most of all.”
—Rabbi Hanina (b. Ta’anit 7a)
PhD Students Advised
- Dr. Anthony Fader • Independent Consultant in NLP • “Open Information Extraction” • 2014
- Dr. Alan Ritter • The Ohio State University • “Information Extraction in Social Media” • 2013
- Dr. Thomas Lin • Microsoft • Leveraging Knowledge Bases in Web Text Processing • 2012
- Dr. Stefan Schoenmackers • eBay • Inference over the Web • 2011
- Dr. Michele Banko • Microsoft • Open Information Extraction for the Web • 2009
- Investigated the problem of extracting information from arbitrary Web text in a scalable, domain-independent manner.
- Dr. Mike Cafarella • University of Michigan • Extracting and Managing Structured Web Data • Co-advisors: Dan Suciu and Alon Halevy • 2009
- Bridged the gap between information extraction and databases.
- Dr. Doug Downey • Northwestern University • Redundancy in Web-scale Information Extraction: Probabilistic Model and Experiment Result • 2008
- Investigated in depth what we can learn from finding extractions repeatedly in the Web corpus.
- Dr. Alex Yates • Temple University • Information Extraction from the Web: Techniques and Applications • 2007
- Investigated the problem of unsupervised synonym resolution on the Web.
- Dr. Ana-Maria Popescu • Pinterest • Information Extraction from Unstructured Web Text • 2007
- Investigated how to extract high-quality information from Web text. Her most impressive demonstration was the Opine system, which extracted product attributes, and associated opinions, from reviews found on-line.
- Dr. Luke McDowell • U.S. Naval Academy • Bringing Meaning to the Masses • Co-advisor: Alon Halevy • 2004
- Investigated how to make the Semantic Web a reality and how to generalize the vision to encompass email as well.
- Dr. Mike Perkowitz • HBO • Adaptive Web Sites • 2000
- Investigated web sites that automatically reconfigure their layout and presentation by analyzing user access patterns recorded in their server logs.
- Dr. Oren Zamir • Google • Clustering Web Documents: A Phrase-Based Method for Grouping Search Engine Results • 1999
- Investigated the use of a novel and fast clustering algorithm to group the results of Web search engines into easily-browsed clusters. The most distinctive aspect of the algorithm was its treatment of documents as strings of words, represented by a suffix tree, in contrast with the standard vector-based representation.
- Dr. Erik Selberg • Microsoft • Towards Comprehensive Web Search • 1999
- Explored meta-search as embodied in MetaCrawler. The dissertation was the first to show (back in WWW4, 1995) that the fraction of the Web covered by individual search engines such as Alta Vista and Lycos was very limited, demonstrating the need for meta-search engines.
- Dr. Keith Golden • NASA Ames, Google • Planning Support for Softbots • 1997
- Investigated novel planning and knowledge representation techniques to support softbots.
- Dr. Neal Lesh • Dimagi • Scalable and Adaptive Goal Recognition • 1997
- Focused on automating the construction of plan libraries adapting techniques from planning and concept learning. His objective was to scale up goal recognition to domains containing millions of plans and goals.
- Dr. Richard Segal • IBM Watson research center • Machine Learning as Massive Search • 1996
- Focused on data mining using massive search: our BRUTE data mining software can analyze over 100,000 hypotheses per second, when run on a SPARC-10.
MA Students Advised
- Tessa Lau • Savioke • “Privacy in a Collaborative Web Browsing Environment” • 1997 • UW PhD with Weld and Domingos, 2001
- Marc Langheinrich • University of Lugano in Switzerland • “A domain independent architecture for efficient information retrieval on the World Wide Web” • 1997 • PhD at the University of Bielefeld
- Jonathan Shakes • Amazon • “Dynamic Reference Sifting: a Case Study in the Homepage Domain” • 1996
- Terrance Goan • Stottler Henke • “Learning About Software Errors” • 1994
Undergraduate Students Advised
- Michael Skinner • Google • 2008
- Michael Schmitz • Allen Institute for AI • 2007
- Kobi Reiter • Google • 2006
- Bao Nguyen • Microsoft • 2005
- Michael Lindmark • Amazon • 2005
- Tessa MacDuff • Google • 2004
- Jeff Lin • Microsoft • 2003
- Gary Lau • Go2Net • 1999
- Zhenya Sigal • Microsoft • 1997
- Christen Boyd • Netbot • 1997
- Darren Schack • Real Networks • 1996
- Adam Loving 1996
- Nick Hart • Real Networks • 1996
- Nels Benson • Japan • 1995
- Dymitr Mozdyniewicz • Quark • 1995
- Guido Hunt 1994
- Greg Fichtenholtz • Hewlett-Packard, Stanford • 1994
- William Alford • PhD program, University of Wisconsin • 1994
- Robert Spiger • Lockheed, AI research center • 1993
- Bruce Lesourd 1993
- Julie Roomy • Hewlett-Packard, OGI • 1993
- Stephen Soderland • PhD program, Umass Amherst, now research scientist at UW CSE • 1992