cv + bio Hal Daumé III
about me cv + bio publications research teaching students software photos calendar contact me links		Curriculum Vita Brief Bio: I am an assistant professor in CS at the University of Utah. My primary research interests are in understanding how to get human knowledge into a machine learning system in the most efficient way possible. In practice, I work primarily in the areas of in Bayesian learning (particularly non-parametric methods), structured prediction and domain adaptation (with a focus on problems in language and biology); I most associate myself with conferences like ACL, ICML, NIPS and EMNLP. I earned my PhD at USC with a thesis on structured prediction for language (my advisor was Daniel Marcu). I spent the summer of 2003 working with Eric Brill in the machine learning group at MSR. Prior to that, I studied math (mostly logic) at CMU. I still like math (perhaps my academic ancestry explains this) and I don't like to use C (instead I use O'Caml or Haskell). I don't like shoes, but I like activities that are hard on your feet: skiing, badminton, Aikido and rock climbing. Here is a version written in third person that is useful for circulation. If you need it more formal, just cut out the last sentence or two. Third Person Bio: Hal Daume III is an assistant professor in the School of Computing at the University of Utah. His primary research interests are in understanding how to get human knowledge into a machine learning system in the most efficient way possible. In practice, he works primarily in the areas of Bayesian learning (particularly non-parametric methods), structured prediction and domain adaptation (with a focus on problems in language and biology). He associates himself most with conferences like ACL, ICML, NIPS and EMNLP. He earned his PhD at the University of Southern Californian with a thesis on structured prediction for language (his advisor was Daniel Marcu). He spent the summer of 2003 working with Eric Brill in the machine learning and applied statistics group at Microsoft Research. Prior to that, he studied math (mostly logic) at Carnegie Mellon University. He still likes math and doesn't like to use C (instead he uses O'Caml or Haskell). He doesn't like shoes, but does like activities that are hard on your feet: skiing, badminton, Aikido and rock climbing. Representative Publications: Hal Daume III, 2009. Bayesian Multitask Learning with Latent Hierarchies. Proceedings of the Conference on Uncertainty in Artificial Intelligence. Hal Daume III, John Langford and Daniel Marcu, 2009. Search-based structured prediction. Machine Learning Journal 75(3). Yee Whye Teh, Hal Daume III and Daniel Roy, 2007. Bayesian agglomerative clustering with coalescents. Proceedings of the Conference on Neural Information Processing Systems. Hal Daume III, 2007. Frustratingly easy domain adaptation. Proceedings of the Conference of the Association for Computational Linguistics. Hal Daume III and Lyle Campbell, 2007. A Bayesian model for discovering typological implications. Proceedings of the Conference of the Association for Computational Linguistics. Hal Daume III and Daniel Marcu, 2006. Domain adaptation for statistical classifiers. Journal of Artificial Intelligence Research. Hal Daume III and Daniel Marcu, 2006. Bayesian query-focused summarization. Proceedings of the Conference of the Association for Computational Linguistics.
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