为加强与国内外统计学者的沟通交流，为我校师生创建一个学习交流的平台，西南财经大学数据科学与商业智能联合实验室将于2023年7月4日举办“2023 Time Series Workshop”。
一、报告嘉宾
（以姓氏首字母排序）
| 姓名 | 学校 | 嘉宾简介 |
| Ching-Kang Ing | Tsinghua University | Ching-Kang Ing is currently a Distinguished Professor with the National Tsing Hua University. His areas of expertise include mathematical statistics, model selection in time series, and high-dimensional data analysis. He has gained international recognition and has won major awards in Taiwan, including the Outstanding Research Awards of the Ministry of Science and Technology (MOST) in 2008 and 2013, the Academia Sinica Investigator Award in 2011, the Science Vanguard Research Award of the MOST in 2016, the Outstanding Scholar Award of Foundation for the Advancement of Outstanding Scholarship in 2017, and the Sun Yat-Sen Academic Award of Sun Yat-Sen Academic and Cultural Foundation in 2020. |
| Dong Li | Tsinghua University | 李东，2010年12月毕业于香港科技大学，2013年9月加入清华大学。主要从事时空数据分析、复杂时间序列分析、机器学习、金融计量学等方面的研究。截止目前，在统计学和计量统计学杂志上共发表SCI及SSCI研究论文40余篇。目前担任中国数学会概率统计分会常务理事、全国工业统计学教学研究会数字经济与区块链技术协会常务理事、中国青年统计学家协会常务理事、北京大数据协会常务理事等；曾任中国数学会概率统计分会副秘书长。 |
| Xiaofeng Shao | University of Illinois at Urbana-Champaign | Xiaofeng Shao received his PhD in Statistics from the University of Chicago in 2006 and has since been a faculty member with the Department of Statistics at the University of Illinois Urbana-Champaign. His current research interests include time series analysis, change-point analysis, functional data analysis, high dimensional data analysis and their applications. He is a fellow of Institute of Mathematical Statistics (IMS) and American Statistical Association (ASA). He currently serves as an associate editor for Journal of Royal Statistical Society, Series B and Journal of Time Series Analysis. |
| Ting Zhang | University of Georgia | Ting Zhang is currently Associate Professor in the Department of Statistics at the University of Georgia. He obtained his Ph.D. in Statistics from The University of Chicago in 2012, and his research interests include tail dependent time series, high-dimensional data, nonparametric and semiparametric inference, nonstationary nonlinear processes, and self-normalization. He has a number of publications in top journals in Statistics and its related fields, and many of them are with his students. He is also the recipient of the prestigious NSF CAREER Award. |
| Xianyang Zhang | Texas A&M University | Xianyang Zhang is an Associate Professor in the statistics department at Texas A&M University. He obtained his Ph.D. in statistics from the University of Illinois at Urbana Champaign in 2013. His research interests include high dimensional/large-scale statistical inference, kernel methods, genomics data analysis, functional data analysis, time series, and econometrics. He currently serves as an associate editor for Biometrics and Journal of Multivariate Analysis. |
| Zhengjun Zhang | University of Wisconsin | Zhengjun Zhang, Professor of Economics and Management in School of Economics and Management at the University of Chinese Academy of Sciences, Professor of Statistics at the University of Wisconsin. He is Fellows of IMS and ASA. |
| Zhou Zhou | University of Toronto | Zhou Zhou obtained his Ph.D. in Statistics from the University of Chicago in 2009. He is currently a Full Professor at the Department of Statistical Sciences, University of Toronto. Zhou's major research interests lie in time series analysis, non- and semi- parametric inference, time-frequency analysis, change point analysis and functional and longitudinal data analysis. |
| Changbo Zhu | University of Notre Dame | Dr. Zhu joined the University of Notre Dame, USA, Department of Applied and Computational Mathematics and Statistics as an assistant professor in 2022. Previously, he spent two years working as a postdoctoral scholar at the University of California, Davis. Dr. Zhu earned his Ph.D. from the University of Illinois at Urbana-Champaign and completed his master’s and bachelor’s degrees from the National University of Singapore. He is interested in solving complex data science problems when data are dependent and naturally lying in some nonlinear spaces. Applications of his research include brain imaging analysis, longitudinal studies, and econometrics. |
二、活动时间
2023年7月3-4日（其中7月3日报到）。
三、面向对象
主要面向本校师生，同时欢迎其他高校数学、统计学、数据科学、经济学、计算机科学等相关专业研究生、青年教师、研究员参加。
四、联系电话
论坛相关咨询请联系028-87352207。
电话：86-028-87352207
地址：四川省成都市青羊区光华村街55号
邮编：610074
西南财经大学 数据科学与商业智能联合实验室 版权所有
蜀ICP备05006386号
