時(shí)間：2025年5月12日（周一）下午15:00

地點(diǎn)：武漢大學(xué)櫻頂老圖書館

主講人：劉軍 美國國家科學(xué)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(xué)獲得數(shù)學(xué)學(xué)士學(xué)位；1991年在美國芝加哥大學(xué)獲統(tǒng)計(jì)學(xué)博士學(xué)位。自2000年至今，擔(dān)任美國哈佛大學(xué)統(tǒng)計(jì)系終身教授，并于2003-2015年兼任哈佛生物統(tǒng)計(jì)系教授。他曾任哈佛統(tǒng)計(jì)系助理教授（1991-1994）；斯坦福大學(xué)統(tǒng)計(jì)系助理教授、副教授、終身教授（1994-2004）；北京大學(xué)數(shù)學(xué)學(xué)院長江講座教授、清華大學(xué)數(shù)學(xué)系訪問教授，并獲國家杰出青年基金B(yǎng)類（2005）。他于2015年領(lǐng)導(dǎo)創(chuàng)建清華大學(xué)統(tǒng)計(jì)學(xué)研究中心，并任名譽(yù)主任至2024年。2024年7月他以籌建發(fā)展委員會(huì)主任身份在清華大學(xué)創(chuàng)建統(tǒng)計(jì)與數(shù)據(jù)科學(xué)系。

劉軍一直從事于貝葉斯統(tǒng)計(jì)理論、蒙特卡洛方法、統(tǒng)計(jì)機(jī)器學(xué)習(xí)、狀態(tài)空間模型和時(shí)間序列、生物信息學(xué)、計(jì)算生物學(xué)等方向的研究，并做出杰出貢獻(xiàn)，對(duì)大數(shù)據(jù)處理和機(jī)器學(xué)習(xí)領(lǐng)域有深遠(yuǎn)影響。他于2002年獲得考普斯會(huì)長獎(jiǎng) （COPSS Presidents' Award，公認(rèn)為國際統(tǒng)計(jì)學(xué)界的最高榮譽(yù)）；2010年獲得世界華人應(yīng)用數(shù)學(xué)最高榮譽(yù)晨興應(yīng)用數(shù)學(xué)金獎(jiǎng)（三年一度，不超過45歲）；2014年被ISI評(píng)為論文高頻引用的數(shù)學(xué)家；2016年獲得泛華統(tǒng)計(jì)協(xié)會(huì)許寶騄獎(jiǎng)（三年一度，不超過51歲）；2004、2005年分別成為美國數(shù)理統(tǒng)計(jì)學(xué)會(huì)和美國統(tǒng)計(jì)學(xué)會(huì)會(huì)士（Fellow）；2022年當(dāng)選國際計(jì)算生物學(xué)會(huì)會(huì)士；2025年當(dāng)選美國國家科學(xué)院院士。劉軍教授還曾任美國統(tǒng)計(jì)協(xié)會(huì)會(huì)刊（JASA）聯(lián)席主編及多個(gè)國際一流統(tǒng)計(jì)雜志副編等職。截至2025年5月，他在各類國際頂尖學(xué)術(shù)雜志（如Science，Nature，Cell，JASA，JMLR等）及書刊上發(fā)表論文300余篇和一本專著，被引用9萬余次（Google scholar）。他已經(jīng)指導(dǎo)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(shù)學(xué)與智能研究院