時間：2025年5月12日（周一）下午15:00
地點：武漢大學櫻頂老圖書館
主講人：劉軍 美國國家科學院院士
題目：Monte Carlo’s View of AI Developments
主講人簡介：
劉軍，1985年于北京大學獲得數學學士學位；1991年在美國芝加哥大學獲統計學博士學位。自2000年至今，擔任美國哈佛大學統計系終身教授，并于2003-2015年兼任哈佛生物統計系教授。他曾任哈佛統計系助理教授（1991-1994）；斯坦福大學統計系助理教授、副教授、終身教授（1994-2004）；北京大學數學學院長江講座教授、清華大學數學系訪問教授，并獲國家杰出青年基金B類（2005）。他于2015年領導創建清華大學統計學研究中心，并任名譽主任至2024年。2024年7月他以籌建發展委員會主任身份在清華大學創建統計與數據科學系。
劉軍一直從事于貝葉斯統計理論、蒙特卡洛方法、統計機器學習、狀態空間模型和時間序列、生物信息學、計算生物學等方向的研究，并做出杰出貢獻，對大數據處理和機器學習領域有深遠影響。他于2002年獲得考普斯會長獎 （COPSS Presidents' Award，公認為國際統計學界的最高榮譽）；2010年獲得世界華人應用數學最高榮譽晨興應用數學金獎（三年一度，不超過45歲）；2014年被ISI評為論文高頻引用的數學家；2016年獲得泛華統計協會許寶騄獎（三年一度，不超過51歲）；2004、2005年分別成為美國數理統計學會和美國統計學會會士（Fellow）；2022年當選國際計算生物學會會士；2025年當選美國國家科學院院士。劉軍教授還曾任美國統計協會會刊（JASA）聯席主編及多個國際一流統計雜志副編等職。截至2025年5月，他在各類國際頂尖學術雜志（如Science，Nature，Cell，JASA，JMLR等）及書刊上發表論文300余篇和一本專著，被引用9萬余次（Google scholar）。他已經指導了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.
承辦單位：武漢數學與智能研究院
