Xiao-Li Meng

Xiao-Li Meng, Ph.D.
Dean of the Graduate School of Arts and Sciences
Whipple V. N. Jones Professor of Statistics
Harvard University
7th Floor, One Oxford Street
Cambridge, MA  02138
Phone: 617-495-1603
Fax: 617-495-1712
Web: http://www.stat.harvard.edu/faculty_page.php?page=meng.html


Xiao-Li Meng photo
>> View Xiao-Li Meng's CV View PDF (contains links to some lecture videos and articles)

Xiao-Li Meng is Dean of the Graduate School of Arts and Sciences and Whipple V. N. Jones Professor of Statistics at Harvard University; previously he taught at The University of Chicago (1991-2001). His degrees include BS (Fudan Mathematics Department, 1982), Master of Science Diploma (Fudan Mathematics Institute, 1986), Master of Art (Harvard Statistics, 1987), and Ph.D. (Harvard Statistics, 1990).

He was the recipient of the 1997-1998 University of Chicago Faculty Award for Excellence in Graduate Teaching, the 2001 COPSS (Committee of Presidents of Statistical Societies) Award, the 2003 Distinguished Achievement Award and the 2008 Distinguished Service Award from the International Chinese Statistical Association, and the 2010 Medallion Lecturer from the Institute of Mathematical Statistics (IMS).

He has served on numerous professional committees, including chairing the 2004 Joint Statistical Meetings and the Committee on Meetings of American Statistical Association (ASA) from 2005-2011. He is an elected fellow of ASA and of IMS. He has also served on editorial boards for The Annals of Statistics, Bayesian Analysis, Bernoulli, Biometrika, Journal of The American Statistical Association, as well as the co-editor of Statistica Sinica. Currently, he is the Statistics Editor for the IMS Monograph and Textbook Series. He is also a co-editor of Applied Bayesian Modeling and Causal Inference from Incomplete-data Perspectives (Gelman and Meng, 2004, Wiley & Sons), Handbook of Markov Chain Monte Carlo (Brooks, Gelman, Jones, and Meng, 2011, Chapman & Hall/CRS), and Strength in Numbers: The Rising of Academic Statistics Departments in the U. S. (Agresti and Meng, 2012, Springer).

His research interests include inference foundations and philosophies, models of all flavors, deterministic and stochastic algorithms, signal extraction in physical, social and medical sciences, and occasionally elegant mathematical statistics. He also writes articles about statistical education and communication, and about professional development.

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