时间：2025年5月12日（周一）下午15:00
地点：911制品厂麻花豆樱顶老图书馆
主讲人：刘军 美国国家科学院院士
题目：Monte Carlo’s View of AI Developments
主讲人介绍：
刘军，1985年于北京大学获得数学学士学位；1991年在美国芝加哥大学获统计学博士学位。自2000年至今，担任美国哈佛大学统计系终身教授，并于2003-2015年兼任哈佛生物统计系教授。他曾任哈佛统计系助理教授（1991-1994）；斯坦福大学统计系助理教授、副教授、终身教授（1994-2004）；北京大学数学学院长江讲座教授、清华大学数学系访问教授，并获国家杰出青年基金叠类（2005）。他于2015年领导创建清华大学统计学研究中心，并任名誉主任至2024年。2024年7月他以筹建发展委员会主任身份在清华大学创建统计与数据科学系。
刘军一直从事于贝叶斯统计理论、蒙特卡洛方法、统计机器学习、状态空间模型和时间序列、生物信息学、计算生物学等方向的研究，并做出杰出贡献，对大数据处理和机器学习领域有深远影响。他于2002年获得考普斯会长奖 （COPSS Presidents' Award，公认为国际统计学界的最高荣誉）；2010年获得世界华人应用数学最高荣誉晨兴应用数学金奖（三年一度，不超过45岁）；2014年被ISI评为论文高频引用的数学家；2016年获得泛华统计协会许宝騄奖（三年一度，不超过51岁）；2004、2005年分别成为美国数理统计学会和美国统计学会会士（Fellow）；2022年当选国际计算生物学会会士；2025年当选美国国家科学院院士。刘军教授还曾任美国统计协会会刊（JASA）联席主编及多个国际一流统计杂志副编等职。截至2025年5月，他在各类国际顶尖学术杂志（如Science，Nature，Cell，JASA，JMLR等）及书刊上发表论文300余篇和一本专著，被引用9万余次（Google scholar）。他已经指导了40多位博士生、30多位博士后。
Brief Introduction of Professor Jun Liu
Jun Liu is Professor of Statistics at Harvard University, with a courtesy appointment at Harvard School of Public Health. Dr. Liu received his BS degree in mathematics in 1985 from Peking University and Ph.D. in statistics in 1991 from the University of Chicago. He held Assistant, Associate, and full professor positions at Stanford University from 1994 to 2004. In 2002, he won the prestigious COPSS Presidents' Award (given annually to one individual under age 40). He was selected as a Medallion Lecturer in 2002, a Bernoulli Lecturer in 2004, a Kuwait Lecturer of Cambridge University in 2008; and elected to Fellow of the Institute of Mathematical Statistics in 2004 and Fellow of the American Statistical Association in 2005. He was awarded the Morningside Gold Medal in Applied Mathematics in 2010 (once every 3 years to an individual of Chinese descent under age 45), and honored with the Outstanding Achievement Award and the Pao-Lu Hsu Award (once every 3 years) by the International Chinese Statistical Association in 2012 and 2016, respectively. In 2017, he was recognized by the Jerome Sacks Award for outstanding Cross-Disciplinary Research, and in 2022 he was elected to Fellow of the International Society of Computational Biology. In 2025, he was elected to the membership of the National Academy of Sciences of the USA.
Dr. Liu and his collaborators introduced the statistical missing data formulation and Gibbs sampling strategies for biological sequence motif analysis in the early 1990s. The resulting algorithms for protein sequence alignments, gene regulation analyses, and genetic studies have been adopted by many researchers as standard computational biology tools. Dr. Liu has made fundamental contributions to statistical computing and Bayesian modeling. He pioneered sequential Monte Carlo (SMC) methods and invented novel Markov chain Monte Carlo (MCMC) techniques. His theoretical and methodological studies on SMC and MCMC algorithms have had a broad impact in many areas. Dr. Liu has also pioneered novel Bayesian modeling techniques for discovering nonlinear and interactive effects in high-dimensional data and led the developments of theory and methods for sufficient dimension reduction in high-dimensions. Dr. Liu has served on numerous grant review panels and editorial boards of leading statistical journals, including the co-editorship of JASA from 2011-2014. Dr. Liu has co-authored over 280 research articles published in leading scientific journals and books, with a Google citation count of more than 90,000 (google scholar). His textbook on the Monte Carlo method is a significant contribution to the fields of computational statistics and machine learning. Additionally, he has mentored 40 PhD students and 32 postdoctoral fellows.
承办单位：武汉数学与智能研究院
