Andrew L Zimdars

zimdars@cs :: Research :: Personal :: Contact :: Links I use :: zimdars.net

This résumé will be available as an Adobe Acrobat document (but not yet).

Objective

Summer or part-time research internships focused on sequential decision problems in complex environments.

Education

University of California, Berkeley — Berkeley, CA
Ph.D., Computer Science (underway)
Carnegie Mellon University — Pittsburgh, PA
B.S., Computer Science (College and University Honors; thesis: The Emergence of Language in Communication Across a Bottleneck)
B.S., Cognitive Science (University Honors)

Skills

Experience

Corporate R & D

BigTribe Corporation — San Francisco, CA
Research intern, April 2002-present
Machine Learning and Applied Statistics, Microsoft Research — Redmond, WA
Research intern, May-August 2000
Natural Language Group, Microsoft Corporation — Redmond, WA
Software design engineer (developer) intern, May-August 1998, May-August 1999
Language Exploitation Technologies, Lockheed Martin Management & Data Systems — Valley Forge, PA
Mission Application Engineer intern, May-August 1997

Teaching

Introduction to Artificial Intelligence, CS 188
University of California, Berkeley, Spring 2002
Research Methods in Cognitive Psychology, 85-310
Carnegie Mellon University, Spring 1999
Introduction to Psychology, 85-102
Carnegie Mellon University, Spring 1998

Publications

Please take a look at my research for more information.

Zimdars, A. L., Chickering, D. M., and Meek, C. (2001). Using temporal data for making recommendations. In Breese, J., and Koller, D. (eds.), Uncertainty in Artificial Intelligence: Proceedings of the Seventeenth Conference. San Francisco: Morgan Kaufmann Publishers.

Noelle, D. C., and Zimdars, A. L. (1999). Methods for learning articulated attractors over internal representations. In Hahn, M., and Stoness, C. (eds.), Proceedings of the 21st Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Lawrence Erlbaum Associates.

Organizations