Yuan Qi
Yuan Qi
Assistant Professor of Computer Science
Assistant Professor of Statistics
Assistant Professor of Biology (courtesy)

Joined department in 2007

Education:
PhD, MIT Media Lab (2005)

Dr. Alan Qi has a joint position in Departments of Computer Science and Statistics. His main research interests include Bayesian learning, computational biology, and other applications of machine learning. Dr. Qi received his PhD in Media Laboratory from the Massachusetts Institute of Technology (MIT) in 2005 and worked a postdoctoral associate at MIT Computer Science and Artificial Intelligence Laboratory from 2005 to 2007.

Dr. Qi has worked extensively on probabilistic graphical models and Bayesian inference. For his Ph.D. research, he worked with T. P. Minka to develop Expectation Propagation algorithms on a variety of graphical models including hybrid dynamic systems, Markov random fields, and conditional random fields. For his postdoctoral research, he collaborated with D.K. Gifford and T.S. Jaakkola on computational biology and Bayesian learning. His recent work focuses on efficient Bayesian methods, such as online learning and parallel inference, for massive data, Gaussian process (and other nonparametric Bayesian) approaches,relational learning on graphs and networks (e.g., biological and social networks), biological pathway modeling and analysis, and SNP analysis.

Dr. Qi has taught at the ACM International Conference on Multimedia, Campus IT Summer School in Spain, and at MIT. He also performed research at MIT, Gatsby unit at the University College London, and Microsoft Research.

He is currently supervising 5 Ph.D. students. His research is supported by two NSF grants, a Showalter Trust award, and a Microsoft award.

Selected Publications
Y. Qi and T.S. Jaakkola, "Parameter Expanded Variational Bayesian Methods", Advances in Neural Information Processing Systems, 19, MIT Press, Cambridge, MA, 2007.
Y. Qi, A. Rolfe, K. D. MacIsaac, G. K. Gerber, D. Pokholok, J. Zeitlinger, T. Danford, R. D. Dowell, E. Fraenkel, T. S. Jaakkola, R. A. Young and D. K. Gifford, "High-resolution Computational Models of Genome Binding Events", Nature Biotechnology, , vol. 24, 963-970, August, 2006.
Y. Qi, M. Szummer, and T. P. Minka, "Diagram Structure Recognition by Bayesian Conditional Random Fields", Proceedings of International Conference on Computer Vision and Pattern Recognition, ,2005.
Funding Administered by Computer Science
Yuan Qi, Genome-wide Examination of Binding Sites for Transcription Factors Responsible for Prostate Cancer Prevention, The Showalter Trust, 7/1/2008-6/30/2010.
Yuan Qi, Integrating Imaging Phenotypes and Genotypes for Early Detection of AD, Indiana University School of Medicine, 3/1/2009-2/28/2010.
Yuan Qi, Integration of relational learning with abinitio methods for prediction of material propoerties, Purdue Research Foundation, 6/1/2009-5/31/2010.
Yuan Qi, Microsoft Gift, Microsoft Corporation, 4/16/2008.
Yuan Qi, RI:Small: Relational Learning and Inference for Network Models, National Science Foundation, 9/1/2009-8/31/2012.
Last Updated: October 05, 2009 10:19pm
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