Chuanhai Liu

Purdue University

Chuanhai Liu earned his PhD in Statistics from Harvard University in 1994. He worked at Bell Laboratories for ten years starting in 1995. Since 2005, he has been a Professor of Statistics at Purdue University. His research interests include the foundations of statistical inference, statistical computing, and applied statistics. Much of his work on iterative algorithms, such as Quasi-Newton, EM, and MCMC methods, is discussed in his book titled "Advanced Markov Chain Monte Carlo Methods" (2010), co-authored with F. Liang and R. J. Carroll. His work on the foundations of statistical inference, developing a new inferential framework for prior-free probabilistic inference, is included in his new book entitled "Inferential Models: Reasoning with Uncertainty," co-authored with R. Martin. For his research on statistical computing, he spent several years experimenting with a multi-threaded and distributed R software system called SupR for big data analysis. Currently, he is working on topics in the area of scientific modeling.

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日期 | 时间 | 会场 | Session | 角色 | 讲题 |
---|---|---|---|---|---|

2024-07-13 | 16:50-17:15 | A301-302 |
Invited Session IS077: Statistical Theory and Learning |
讲者 | Estimation of Over-parameterized Models from an Auto-Modeling Perspective |