## Long NguyenAssociate Professor and Director of Master's programsDepartment of Statistics, University of Michigan Other affiliations:
Mail Address: 439 West Hall, 1085 South University, Ann Arbor, MI 48109-1107 |

**Prospective PhD students:** Thank you for your interest. Admissions decision is
made a graduate admissions committee, please see
this link for further information. My apology if I am unable to respond to your enquiry
due to the large volume of such emails.

- Nonparametric Bayesian statistics
- Machine learning and optimization
- Hierarchical, mixture and graphical models
- Spatiotemporal and functional data analysis
- Stochastic, variational and geometric methods in statistical inference

Robust estimation of mixing measures in finite mixture models. N. Ho, X. Nguyen and Y. Ritov. arXiv:1709.08094. Conic scan-and-cover algorithms for nonparametric topic modeling. M. Yurochkin, A. Guha and X. Nguyen. *Advances in NIPS 30*, 2017.Multi-way interacting regression via factorization machines. M. Yurochkin, X. Nguyen and N. Vasiloglou. *Advances in NIPS 30*, 2017.Multilevel clustering via Wasserstein means. N. Ho, X. Nguyen, M. Yurochkin, H. H. Bui, V. Huynh and D. Phung. *Proceedings of the ICML*, 2017.In-database learning with sparse tensors M. Abo Khamis, H. Q. Ngo, X. Nguyen, D. Olteanu and M. Schleich. To appear, *Proceedings of PODS*, 2018.Singularity structures and impacts on parameter estimation in finite mixtures of distributions. N. Ho and X. Nguyen. arXiv:1609.02655. -
Borrowing strength in hierarchical Bayes: posterior concentration of the Dirichlet base measure.
X. Nguyen.
*Bernoulli*, 22(3), 1535--1571, 2016. -
Geometric Dirichlet means algorithm for topic inference. M. Yurochkin and X. Nguyen. *Advances in NIPS 29*, 2016. -
Scalable nonparametric Bayesian multilevel clustering. V. Huynh, D. Phung, S. Venkatesh, X. Nguyen, M. Hoffman and H. H. Bui. *Proceedings of UAI*, 2016. -
On the consistency of inversion-free parameter estimation for Gaussian random fields. H. Keshavarz, C. Scott and X. Nguyen. *Journal of Multivariate Analysis*, 150, 245--266, 2016. -
Convergence rates of parameter estimation for some weakly identifiable finite mixtures. N. Ho and X. Nguyen. *Annals of Statistics*, 44(6), 2726--2755, 2016. -
On strong identifiability and convergence rates of parameter estimation in finite mixtures. N. Ho and X. Nguyen. *Electronic Journal of Statistics*, 10(1), 271--307, 2016. -
Optimal change point detection in Gaussian processes.
H. Keshavarz, C. Scott and X. Nguyen.
To appear,
*Journal of Statistical Planning and Inference*. -
Posterior contraction of the population polytope in finite admixture
models.
X. Nguyen.
*Bernoulli*, 21(1), 618--646, 2015. -
Parallel feature selection inspired by group testing.
Y. Zhou, C. Zhang, U. Porwal, H. Q. Ngo, X. Nguyen, C. Ré,
and V. Govindaraju.
*Advances in NIPS 27*, 2014. -
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. -
Understanding the limiting factors of topic modeling via posterior contraction analysis.
J. Tang, Z. Meng, X. Nguyen, Q. Mei and M. Zhang.
*Proceedings of the ICML*, 2014. -
Bayesian nonparametric modeling for functional analysis of variance.
X. Nguyen and A. E. Gelfand.
*Annals of the Institute of Statistical Mathematics*, 66(3), 496--526, 2014. -
Bayesian inference as iterated random functions with applications to sequential inference in graphical models
A. A. Amini and X. Nguyen.
*Advances in NIPS 26*, 2013. -
Convergence of latent mixing measures in finite and infinite mixture models.
X. Nguyen.
*Annals of Statistics*, 41(1), 370--400, 2013. [Corrections] -
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 Trans 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 ...

- Elements of data science Summer School on Data Science, Vietnam Institute for Advanced Study in Mathematics, Hanoi and Ho Chi Minh, May 2017.
- Multi-level clustering with contexts via hierarchical nonparametric Bayesian inference. Biostatistics Seminar, University of Michigan, October 2016.
- Singularity structures and parameter estimation in finite mixture models. Workshop on Empirical Likelihood Methodology, National University of Singapore, June 2016.
- Topic modeling with more confidence: a theory and some algorithms. Keynote talk, Pacific-Asia Knowledge Discovery and Data Mining Conference, Ho Chi Minh, May 2015.
- Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. 9th 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. [Additional notes ]
- 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.

- Nhat Ho PhD 2017, joint with Ya'acov Ritov; Postdoctoral fellow, University of California, Berkeley
- Hossein Keshavarz PhD 2017, joint with Clay Scott; Postdoctoral fellow at the IMA, University of Minnesota
- Federico Camerlenghi Postdoctoral visiting scholar, April--May 2016; Assistant Professor, University of Milano-Bicocca
- Zhaoshi Meng PhD 2014, joint with Al Hero; Senior Researcher, Vicarious, CA
- Arash Ali Amini Postdoctoral fellow 2011--2014; Assistant Professor, University of California, Los Angeles
- Vijay Manikandan Janakiraman PhD 2013, joint with Dennis Assanis; Research Scientist, NASA's Ames Research
- Jian Tang Visiting PhD student from Peking University 2012--2013; Assistant Professor, Université de Montréal
- Kohinoor Dasgupta, PhD 2012, joint with Vijay Nair and Stilian Stoev; Senior Biostatistician, Novartis India
- Cen Guo, PhD 2012, joint with Tailen Hsing; Data Scientist, Uber, CA
- Bopeng Li, MS 2012; in Statistics PhD program, University of Michigan
- Hyun-Chul Kim, Visiting Scholar 2010--2011; Research Professor, Yonsei University, Korea

- Associate Editor work
- Bayesian Analysis,
- Annals of the Institute of Statistical Mathematics,
- SIAM Journal on Mathematics of Data Science,
- Journal of Machine Learning Research

- Program Committee's Area Chair: AISTATS (2015, 2017), ICML (2015, 2017, 2018), IJCAI (2016)
- Formative education in Hai Phong (Vietnam), Bachelor's degree from POSTECH (Korea)
- Master's degree from Arizona State University, apprenticing with Subbarao Kambhampati
- Ph.D, University of California, Berkeley, advised by Michael Jordan and Martin Wainwright
- Postdoctoral fellow at SAMSI and Duke University, mentored by Alan Gelfand and Jim Clark

- Big Data Summer Institute at the University of Michigan. Exciting opportunity for computer science, mathematics and statistics undergraduates looking to find meaning in very large scale data.
- Vietnam Institute for Advanced Study in Mathematics. An excellent place for mathematics and mathematical research in Hanoi.
- Real time CO2 data assimilation 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. Very informative resources.

Last updated on September 7, 2015 by XuanLong Nguyen (Nguyễn Xuân Long)