Associate Professor, Department of Computer Science, University of Massachusetts Amherst, (2003-present)
Research Associate Professor, Department of Computer Science, University of Massachusetts Amherst, (2002-2003)
VP, Research and Development WhizBang! Labs; Director, WhizBang! Labs, East, (2000-2002.)
Adjunct Faculty, Carnegie Mellon University, Center for Automated Learning and Discovery & Language Technologies Institute, (1998-present).
Research Scientist, Research Coordinator, Just Research (aka JPRC), (1997-2000).
Postdoc, Carnegie Mellon, Computer Science with Sebastian Thrun and Tom Mitchell, 1996.
Ph.D., University of Rochester, Computer Science, with Dana Ballard, 1995.
B.A., Dartmouth College, 1989.
H.S., NCSSM, 1985.
A bio from the preface to my Ph.D. thesis (1995).
A more recent bio.
Baby Pictures of my sister and me.
Pictures of my son Theo, born April 10, 1999.
|Work:||(413) 545-1323, FAX: (413) 545-1789. Dept. of Computer Science, 140 Governors Drive, UMass, Amherst, MA 01003. Map,|
|Home:||(413) 549-7808, 128 Cottage Street, Amherst, MA 01002. Map.|
I was the leader of the project at JustResearch that created Cora, a domain-specific search engine over computer science research papers. It currently contains over 50,000 postscript papers. You can read more about our research on Cora in our IRJ journal paper or a paper presented at the AAAI'99 Spring Symposium. The Cora team also included Kamal Nigam, Kristie Seymore, Jason Rennie, Huan Chang and Jason Reed.
I have been invited to give a tutorial at the Neural Information Processing Systems conference (NIPS*2002). The title is
"Information Extraction from the World Wide Web".
With Lillian Lee, Tony Jebara and Kamal Nigam, I co-organized IJCAI'2001 workshop titled Text Learning: Beyond Supervision.
With Thorsten Joachims, Mehran Sahami and Lyle Ungar, I co-organized a IJCAI-99 workshop on Machine Learning for Information Filtering.
With Rich Caurana, Virginia de Sa and Michael Kearns, I co-organized a NIPS*98 workshop on "Integrating Supervised and Unsupervised Learning".
With Mehran Sahami, Mark Craven and Thorsten Joachims I co-organized a ICML/AAAI-98 workshop on Learning for Text Categorization.
It is related to Ron, Singer and Tishby's Probabilistic Suffix Trees, Leslie Kaelbling's G-algorithm and Andrew Moore's Parti-game. It is distinguished from similar-era work by Michael Littman, Craig Boutilier and others in that it learns both a model and a policy, and is quite practical with infinite-horizon tasks and large state and observation spaces. Follow-on or comparison work has been done by Anders Jonsson, Andy Barto, Will Uther, Leslie Pack Kaelbling, Natalia Hernandez, and Sridhar Mahadevan.
The algorithm, called U-Tree, was demonstrated solving a highway driving task using simulated eye-movements and deictic representations. The simulated environment has about 21000 states, 2500 observations, noise and much hidden state. After about 2 1/2 hours of simulated experience, U-Tree learns a task-specific model of the environment that has only 143 states.