Larry Alan Wasserman (born 1959) is a Canadian-American statistician and a professor in the Department of Statistics & Data Science and the Machine Learning Department at Carnegie Mellon University. Biography Wasserman received his Ph.D. from the University of Toronto in 1988 under the supervision of Robert Tibshirani. He received the COPSS Presidents' Award in 1999 and the CRM-SSC Prize in 2002. He was elected a fellow of the American Statistical Association in 1996, of the Institute of Mathematical Statistics in 2004, and of the American Association for the Advancement of Science in 2011. He was elected to National Academy of Sciences in May, 2016. Selected works Wasserman has written many research papers about nonparametric inference, asymptotic theory, causality, and applications of statistics to astrophysics, bioinformatics, and genetics. He has also written two advanced statistics textbooks, All of Statistics and All of Nonparametric Statistics. 2004. All of Statistics: A Concise Course in Statistical Inference. Springer-Verlag, New York. won DeGroot Prize 2005. 2006. All of Nonparametric Statistics. Springer. 2013. Topological Inference. Reitz Lecture 2013. Honors and awards 2016, Member of National Academy of Sciences Wasserman was elected to National Academy of Sciences in recognition of his distinguished and continuing achievement in original research. See also Peer review Computational thinking References External links Wasserman's home page Wasserman's Blog on Statistics and Machine Learning Canadian statisticians Fellows of the Institute of Mathematical Statistics Fellows of the American Statistical Association Members of the United States National Academy of Sciences Carnegie Mellon University faculty Living people University of Toronto alumni Scientists from Ontario 21st-century Canadian mathematicians 1959 births Mathematical statisticians