短课邀请 | 第四届统计与数据科学联合会议系列短课通知（第一轮）

时间：2026年7月5日-9日（7月4日报到）

地点：贵州财经大学

本次短课共5天，每天由两位统计与数据科学领域的专家在上下午分别授课3小时，授课日程及专家简介（按课程顺序）如下。

       严晓东，西安交通大学数学与统计学院教授，博士生导师，入选国家级青年人才项目和校内青拔A类支持计划，滴滴盖亚学者, 研究方向为智能体统计学，包括智能计算和智能推断等，目前兼任中关村软联智能算法委员会秘书长，学术成果发表在统计学著名期刊JRSSB,AOS,JASA和经济学著名期刊JOE等。在高等教育出版社以独立主编出版了《机器学习》《数据科学实践基础-基于R》和《大模型学习科研手册》三部教材或专著。

       常晋源，西南财经大学光华首席教授，国家杰青、享受国务院政府特殊津贴专家，四川省基础研究领衔科学家，教育部中央高校优秀青年团队带头人，主要从事大规模复杂数据分析相关的研究。先后担任统计学、计量经济学和运筹管理国际顶级学术期刊Journal of the Royal Statistical Society Series B、Journal of Business & Economic Statistics、Journal of the American Statistical Association和Operations Research的副主编，获霍英东教育基金会高等院校青年教师奖一等奖和青年科学奖一等奖、教育部高等学校科学研究优秀成果奖、四川省青年科技奖等多项奖励。

 Yao Xie is the Coca-Cola Foundation Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, and Associate Director of the Machine Learning Center (ML@GT). She received her Ph.D. in Electrical Engineering, with a minor in Mathematics from Stanford University, and was previously a Research Scientist at Duke University. Her research develops theory-grounded and computationally efficient methods for sequential inference and decision-making in high-dimensional and spatio-temporal settings, with an emphasis on change-point detection and uncertainty quantification. More recently, she has been integrating generative modeling and modern AI frameworks to enable robust inference and prediction in complex systems.

 Her work has been recognized by the C. W. S. Woodroofe Award (2024) and the INFORMS Gaver Early Career Award (2022). She is also a Member of the 2026 Cohort of the National Academies’ New Voices in Sciences, Engineering, and Medicine program and the IEEE Information Theory Society Distinguished Lecturer for 2026–2027. She serves as an Associate Editor for IEEE Transactions on Information Theory, Journal of the American Statistical Association—Theory and Methods, The American Statistician, Operations Research, Annals of Applied Statistics, Sequential Analysis, and INFORMS Journal on Data Science, and as an Area Chair for NeurIPS, ICML, and ICLR, and a Senior Program Committee Member for AAAI.

      Gen Li is an Assistant Professor in the Department of Statistics at the Chinese University of Hong Kong. Previously, he was a postdoctoral researcher in the Department of Statistics and Data Science at the Wharton School at University of Pennsylvania, co-advised by Professor Yuxin Chen and Professor Yuting Wei. He received his Ph.D. in the Department of Electronic Engineering at Tsinghua University, advised by Professor Yuantao Gu. Before his Ph.D., he received his bachelor's degree from the Department of Electronic Engineering and Department of Mathematics at Tsinghua University in 2016. He is interested in diffusion based generative model, reinforcement learning, high-dimensional statistics, machine learning, signal processing, and mathematical optimization.

       张新雨，中国科学院数学与系统科学研究院研究员。2010年在中科院系统所获博士学位，曾是TAMU博士后和PSU的Research Fellow。担任期刊《Journal of Systems Science and Complexity》领域主编、期刊《Statistical Analysis and Data Mining》Associate Editor、期刊《系统科学与数学》和《应用概率统计》编委，是中国统筹法优选法与经济数学研究会数据科学分会副理事长和国际统计学会当选会员。先后主持国家自然科学基金委优秀和杰出青年研究基金项目，曾获得中国管理学青年奖和中科院优秀博士学位论文等奖励。主要从事统计学和计量经济学的理论和应用研究工作,具体研究方向包括模型平均、机器学习、组合预测和卫生统计等。发表了50多篇学术论文,其中20余篇论文发表在Annals of Statistics、Biometrika、JASA、JRSSB、Journal of Econometrics和Econometric Theory。

       周帆，上海财经大学统计与数据科学学院副教授，教育部青年长江学者，博士毕业于美国北卡罗来纳大学教堂山分校，现担任统计学顶刊JASA的编委。研究兴趣包括深度学习，强化学习的算法与理论，时空网络，因果推断，在包括JASA，JMLR,NeurlPS, ICML,ICLR等统计学，机器学习顶刊和顶会上发表了数十篇文章，曾获泛华统计协会国际会议新研究者奖,UNCJames E. Grizzle Distinguished Alumnus Award和Barry H.Margolin Award.

      Cong Ma is an assistant professor in the Department of Statistics at the University of Chicago. Previously, he was a postdoctoral researcher at UC Berkeley, advised by Professor Martin Wainwright. he obtained his Ph.D. at Princeton University in 2020, advised by Professor Yuxin Chen and Professor Jianqing Fan. Prior to the graduate school, he received his bachelor's degree in Electrical Engineering from Tsinghua University in 2015. He is broadly interested in mathematics of data science with a current focus on reinforcement learning, transfer learning, multi-modal learning, high-dimensional statistics, and nonconvex optimization.

      Peng Ding is an associate professor in the Department of Statistics at UC Berkeley. He obtained his Ph.D. from the Department of Statistics, Harvard University in May 2015, and worked as a postdoctoral researcher in the Department of Epidemiology, Harvard T. H. Chan School of Public Health until December 2015. Previously, he received his B.S. (Mathematics), B.A. (Economics), and M.S. (Statistics) from Peking University.

      His research expertise and interest is statistical causal inference, missing data, Bayesian statistics, applied statistics.

       Yong Chen is the tenured Professor of Biostatistics and the Founding Director of the Center for Health Analytics and Synthesis of Evidence (CHASE) at the University of Pennsylvania. He is an elected fellow of American Statistical Association, International Statistical Institute, Society for Research Synthesis Methodology, American College of Medical Informatics, and American Medical Informatics Association. He founded the Penn Computing, Inference and Learning (PennCIL) lab at the University of Pennsylvania, focusing on clinical evidence generation and evidence synthesis using clinical and real-world data. Dr. Chen’s group has pioneered innovative approaches to the sharing of aggregated data to advance multi-center clinical research and he has extensive experience with conductive research on clinical evidence generation using large scale observational data (including EHR and claims data). 

       涂云东,北京大学光华管理学院和北京大学统计科学中心联席教授。入选“日出东方”北大光华青年人才,教育部“长江学者奖励计划”青年长江学者，国家杰出青年科学基金获得者。北京大学优秀研究生导师(2024)，EconometricReviews Scholar(2024)，三次获评北京大学优秀博士学位论文指导教师 (2017,2021,2024)。2004年和2006年先后获武汉大学理学学士学位和经济学硕士学位，2012年获美国加州大学河滨分校经济学博士学位。亚太青年计量经济学者会议发起人和主要组织者。40 余篇学术论文发表在多个国际国内知名专业杂志。著作教材《时间序列分析》由人民邮电出版社于 2022年9月出版。研究领域涵盖时间序列分析、非参数计量方法、大数据分析、金融计量和预测等。

• 高年级本科生（本科三年级及以上）；

• 硕士/博士研究生；

• 青年教师及青年学者。

本届短课计划招收学员150-200名。

1. 报名方式：请扫描文末二维码进行报名。

2. 截止时间：报名截止日期为2026年4月30日，建议尽早完成信息填写。

3. 录取方式：材料审核通过后，采取滚动录取方式，先到先审，录满为止。录取通过后我们将通过邮件发送录取通知。

4. 培训费用：学员须在收到录取通知后的10个工作日内，缴纳培训费人民币1000元。具体缴费方式将在录取通知邮件中说明，缴费完成视为正式报名成功。

5. 食宿安排：课程期间食宿将由会务组统一协调安排，费用需学员自理。

联席主席

Yuxin Chen（宾夕法尼亚大学）

王汉生（北京大学）

主办单位

贵州财经大学数学与统计学院