Meng, X.L. (2018) Conducting Highly Principled Data Science: A statistician's job and joy. Statistics and Probability Letters,136, 51-57. X. Xie and Meng, X.L. (2017) Dissecting Multiple …

Curriculum Vitae of Xiao-Li Meng . Mail Address: Department of Statistics, Harvard University . Science Center, 4th Floor, 1 Oxford Street . Cambridge, MA 02138, U.S.A. Contact: [email protected]; 617-495-1603 (O); 617-495-1712 (fax) Education: November 1990 Ph.D. in Statistics – Harvard University (Advisor: D.B. Rubin)

“The Data Science Revolution: An Interview with Xiao-Li Meng” The Scholarly Kitchen by Roger Schoenfeld (Jan 16, 2020) (Based on Live Interview conducted on Dec 4, 2019 by Kevin Guthrie, President of ITHAKA, at ITHAKA Next Wave 2019: Leading Change.).

of individualized predictions with Big Data will be treated in the sequel, Meng (2018). For population inferences, a key “policy proposal” of the current paper is to shift from our traditional focus on assessing probabilistic uncertainty (e.g., in a sample mean) in the familiar form of Standard Error ∝ σ √ n

2007 – Whipple V.N. Jones Professor of Statistics, Department of Statistics, Harvard University . 2004 – 2012 Chair, Department of Statistics, Harvard University (on leave 2010-2011)

2020年4月24日 · Many congratulations to our own Professor Xiao-Li Meng, elected April 23, 2020 as a Fellow of the American Academy of Arts and Sciences. Read more about this honor in the Harvard Gazette.

The Institute of Mathematical Statistics has selected Professor Xiao-Li Meng as their President-Elect (weblink http://bulletin.imstat.org/2017/07/ims-election-results/). His term as President starts in July 2018.

Read more about Xiao-Li Meng. SC 300C. [email protected] . p: (617) 495-1603. Susan Murphy. Mallinckrodt Professor of Statistics and of Computer Science, Associate Faculty, Kempner Institute, Harvard University Joint Director of Graduate Studies.

Colloq: Xiao-Li Meng Date: Monday, October 17, 2016, 4:15pm to 5:15pm. Location: Science Center Rm. 300H. Statistical Paradises and Paradoxes in Big Data. Statisticians are increasingly posed seemingly paradoxical questions, challenging our qualifications for entering the statistical paradises created by Big Data.

Professor Meng was on the faculty of the University of Chicago for ten years, and in the year 2001 he returned to Harvard, where he is now the chairman of the Statistics Department. Professor Meng is the 2001 COPSS winner, recipient of the 2003 ICSA Distinguish Achievement Award,