Long Nguyen Assistant Professor, Department of Statistics, Dept of Electrical Engineering and Computer Science (by courtesy), University of Michigan Email: xuanlong@umich.edu Office: 456 West Hall, Phone: 734-763-3499, Fax: 734-763-4676 Mail Address: 439 West Hall, 1085 South University, Ann Arbor, MI 48109-1107

[Research] [Teaching] [Students] [Publications] [Biography]

• Statistical Machine Learning reading group
• Dept of Statistics Seminar Series

Research interests

• Nonparametric Bayesian statistics
• Variational and decentralized statistical inference
• Machine learning in networks and distributed systems
• Analysis of signals, texts, images and other spatio-temporal and functional data

A biased sample of papers

• Bayesian nonparametric multilevel clustering with group-level contexts. V. Nguyen, D. Phung, X. Nguyen, S. Venkatesh and H. H. Bui. Proceedings of the ICML, 2014.
• Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. X. Nguyen. Technical Report No. 532, Dept of Statistics, Univ of Michigan, January 2013.
• Bayesian inference as iterated random functions with applications to sequential inference in graphical models. A. A. Amini and X. Nguyen. Advances in Neural Information Processing Systems (NIPS) 26, 2014.
• Posterior contraction of the population polytope in finite admixture models. X. Nguyen. To appear, Bernoulli.
• Bayesian nonparametric modeling for functional analysis of variance. X. Nguyen and A. E. Gelfand. Annals of the Institute of Statistical Mathematics, DOI:10.1007/s10463-013-0436-7, 2013.
• Convergence of latent mixing measures in finite and infinite mixture models . X. Nguyen. Annals of Statistics, 41(1), 370--400, 2013.
• Sequential detection of multiple change points in networks: A graphical model approach. A. A. Amini and X. Nguyen. IEEE Transactions on Information Theory, 59(9), 5824--5841, 2013.
• The Dirichlet labeling process for clustering functional data. X. Nguyen and A. E. Gelfand. Statistica Sinica 21(3), 1249--1289, 2011.
• Inference of global clusters from locally distributed data. X. Nguyen. Bayesian Analysis, 5(4), 817--846, 2010.
• Estimating divergence functionals and the likelihood ratio by convex risk minimization. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE Transactions on Information Theory, 56(11), 5847--5861, 2010.
• On surrogate loss functions and f-divergences. X. Nguyen, M. J. Wainwright and M.I. Jordan. Annals of Statistics, 37(2), 876--904, 2009.

• More ...

Selected talk slides

• Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. Bayesian Nonparametrics conference, Amsterdam, June 2013.
• Convergence of latent mixing measures in finite and infinite mixture models. Bayesian Nonparametrics Workshop at ICERM, Providence, September 2012.
• Clustering problems, mixture models and Bayesian nonparametrics. VIASM Summer School, Hanoi, July 2012. [Slides 1 ] [Notes 2 ]
• Message-passing sequential detection of multiple change points in networks. IEEE Symposium on Information Theory, Boston, July 2012.
• Inference of functional clusters from non-functional data . Midwest Statistics Research Colloquium, Madison, March 2012.
• Dirichlet labeling and hierarchical processes for clustering functional data . IMS-China Conference, Xi'an, July 2011.
• Decentralized decision making with spatially distributed data . AI Seminar, University of Michigan, Oct 2009.
• Surrogate loss functions, divergences and decentralized detection. Thesis talk, UC Berkeley, May 2007.
• Anomaly and sequential detection with time series data . Tutorial lectures given at Berkeley, 2006.

Biographical information

• Ph.D, UC Berkeley, 2007; Postdoctoral fellow, SAMSI/ Duke University, 2007--2009
• Best Paper Award, 21st International Conference on Machine Learning, 2004
• Young Author's Best Paper Award by the IEEE Signal Processing Society, 2007
• Leon O. Chua Award for outstanding achievement in an area of nonlinear science, UC Berkeley, 2007
• CAREER Award, National Science Foundation, Division of Mathematical Sciences, 2014--2019
• Best Paper Award, 31st International Conference on Machine Learning, 2014

• Associate Editor, Bayesian Analysis

Students

• Nhat Minh Ho
• Hossein Keshavarz (joint with Clay Scott)
• Zhaoshi Meng (joint with Al Hero)
• Mikhail Yurochkin

• Arash Ali Amini (Postdoctoral fellow 2011--2014; Assistant Professor, UCLA)
• Vijay Manikandan Janakiraman (PhD 2013, joint with Dennis Assanis; Research Scientist, NASA's Ames Research)
• Kohinoor Dasgupta (PhD 2012, joint with Vijay Nair and Stilian Stoev; Senior Biostatistician, Novartis India)
• Cen Guo (PhD 2012, joint with Tailen Hsing; Senior Analyst, United Airlines, Chicago)
• Hyun-Chul Kim (Visiting Scholar 2010--2011; Research Professor, Yonsei University, Seoul)
• Jian Tang (Visiting PhD student from Peking University 2012--2013; Researcher, Microsoft Research Asia, Beijing)
• Bopeng Li (MS 2012; in Statistics PhD program, University of Michigan)

Links

• Real time CO2 data assimulation and anomaly detection project Led by Anna Michalak Lab at Carnegie Institution for Science and Michigan team
• STATMOS: Research Network for Statistical Methods for Atmotspheric and Oceanic Sciences
• Pointers on nonparametric Bayesian statistics Collected by Peter Orbanz
• Summer School: Modern statistical methods in machine learning Vietnam Institute for Advanced Study in Mathematics, Summer 2012
• Lexicon in probability, statistics and machine learning: Xác suất, thống kê và học máy (in Vietnamese)