Organization:

• Hal Daumé III, Information Sciences Institute
• Yee Whye Teh, National University of Singapore

• Kenneth Church, Microsoft Research

  Ken Church moved to Microsoft Research in late 2003. Before that, he was the head of a data mining department in AT&T Labs-Research (formally AT&T Bell Labs, Murray Hill, NJ). Church received his BS, Masters and PhD from MIT in computer science in 1978, 1980 and 1983, and immediately joined AT&T. He has worked in many areas of computational linguistics including: acoustics, speech recognition, speech synthesis, OCR, phonetics, phonology, morphology, word-sense disambiguation, spelling correction, terminology, translation, lexicography, information retrieval, compression, language modeling and text analysis. He enjoys working with very large corpora such as the Associated Press newswire (1 million words per week) and larger datasets such as larger data sets such as telephone call detail (1-10 billion records per month).

• Tom Griffiths, Brown University

  Tom Griffiths is interested in developing rational accounts of cognition using probabilistic generative models and Bayesian statistics. His current areas of interest are understanding people's everyday inductive leaps -- difficult inductive problems we solve every day, like predicting the future, learning causal relationships, and noticing coincidences -- and the interface between psychology and machine learning in developing statistical models of language.

• Andrew McCallum, University of Massachusetts Amherst

  The main goal of Andrew McCallum's research is to dramatically increase our ability to mine actionable knowledge from unstructured text. He is especially interested in information extraction from the Web, understanding the connections between people and between organizations, expert finding, social network analysis, and mining the scientific literature & community. Toward this end his group develops and employs various methods in statistical machine learning, natural language processing, information retrieval and data mining, tending toward probabilistic approaches and graphical models.

• Kenneth Church, Microsoft Research
• Tom Griffiths, Brown University
• Jeff Bilmes, University of Washington
• Andrew McCallum, University of Massachusetts at Amherst
• Sam Roweis, University of Toronto

• Peter Sunehag, NICTA/ANU Canberra
• Yee Whye Teh, National University of Singapore
• David Vickrey, Stanford University
• Hanna Wallach, University of Cambridge
• Shaojun Wang, University of Alberta
• Davy Weissenbacher, Universite Paris-Nord