Xiao-Li Meng stands as a preeminent leader in statistical science whose work bridges theoretical rigor with transformative educational innovation and interdisciplinary application. He currently holds the distinguished Whipple V. N. Jones Professorship of Statistics at Harvard University, a position he attained after returning from the University of Chicago where he served on the faculty from 1991 to 2001. His academic foundation was established at Fudan University where he earned his B.Sc. in mathematics in 1982, followed by doctoral studies at Harvard that yielded a Ph.D. in statistics in 1990. Meng's leadership at Harvard extended from 2004 to 2012 as Chair of the Department of Statistics, during which he pioneered innovative courses designed to transform students' perceptions of statistics, and subsequently from 2012 to 2018 as Dean of the Graduate School of Arts and Sciences.
Meng's research contributions have fundamentally shaped modern statistical methodology, particularly through his influential work on Markov chain Monte Carlo algorithms and the theoretical foundations that connect Bayesian, Fiducial, and frequentist perspectives. He has developed critical frameworks for multi-source, multi-phase, and multi-resolution inferences that address complex contemporary data challenges across numerous domains including astronomy, astrophysics, mental health services assessment, and genetic studies. With over 150 publications spanning a dozen theoretical and methodological areas, his specific technical contributions including posterior predictive p-values, extensions to the EM algorithm, and bridge and path sampling methods have become essential tools in computational statistics. His exceptional scholarly impact was recognized with the prestigious COPSS Presidents' Award in 2001, considered the highest honor for a statistician under age forty.
Beyond his scholarly contributions, Meng has profoundly influenced the statistical community through his commitment to communication, education, and interdisciplinary collaboration. As the Founding Editor-in-Chief of Harvard Data Science Review, he has created a premier platform for advancing discourse at the intersection of statistics, computation, and domain sciences. His engaging communication style is evident in his more than 400 research presentations and public speeches, as well as his widely read "The XL-Files" column in the Institute of Mathematical Statistics Bulletin that makes complex statistical concepts accessible and entertaining. Currently, Meng continues to advance the philosophical foundations of statistical inference while exploring innovative methodologies for signal extraction and uncertainty assessment across natural, social, and medical sciences, ensuring his enduring legacy in statistics education and methodology will continue to guide future generations of data scientists.
