Keynote speaker 1：

    Tianxi Cai, Harvard University

    Tianxi Cai is a major player in developing analytical tools for mining EHR data and predictive modeling with biomedical data. She provides statistical leadership on several large-scale projects, including the NIH-funded Undiagnosed Diseases Network at DBMI. Cai's research lab develops novel statistical and machine learning methods for several areas including clinical trials, real world evidence, and personalized medicine using genomic and phenomic data. Cai received her ScD in Biostatistics at Harvard and was an assistant professor at the University of Washington before returning to Harvard as a faculty member in 2002.

https://www.hsph.harvard.edu/profile/tianxi-cai/

Keynote speaker 2：

    Will Cong, Cornell University

    Will Cong is the Rudd Family Professor of Management, professor of finance, and founding director of the FinTech Initiative at Cornell University. He is also a finance editor at the Management Science, faculty scientist at the Initiative for Cryptocurrencies & Contracts (IC3), research associate at the NBER, founder of multiple international research forums, a former Kauffman Junior Fellow, Poets & Quants World Best Business School Professor, and 2022 Top 10 Quant Professor.   
    Cong's research spans financial economics, information economics, fintech, digital economy, and entrepreneurship. He and his coauthors have pioneered the introduction of goal-oriented search and interpretable AI for finance, laid the foundations of tokenomics (covering categorization of tokens, cryptocurrency pricing, central bank digital currencies/payment systems, and optimal token monetary policy design), analyzed centralization issues and dynamic incentives in blockchains and DeFi, and developed data analytics for detecting market manipulation and better fintech regulation among others.

Keynote speaker 3:

    Weinan E, Peking University

    A renowned mathematician, Academician of the Chinese Academy of Sciences, Chair Professor at Peking University, Director of the National Engineering Laboratory for Big Data Analysis and Applications, Director of the International Center for Machine Learning at Peking University, President of the Beijing Institute of Scientific Intelligence, President of the Beijing Big Data Research Institute, Advisor to the Chinese Society for Industrial and Applied Mathematics, and Chair of the Academic Committee at the Wuhan Institute of Mathematics and Intelligence. He was formerly a professor in the Department of Mathematics and at the Program in Applied and Computational Mathematics at Princeton University.
    His primary research areas include computational mathematics, applied mathematics, machine learning, and their applications in fields such as mechanics, physics, chemistry, and materials science.

https://www.math.pku.edu.cn/jsdw/js_20180628175159671361/e_20180628175159671361/138270.htm

    James M. Robins, Harvard University

    James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials, particularly those in which the treatment varies with time. He is the 2013 recipient of the Nathan Mantel Award for lifetime achievement in statistics and epidemiology, and a recipient of the 2022 Rousseeuw Prize in Statistics, jointly with Miguel Hernán, Eric Tchetgen-Tchetgen, Andrea Rotnitzky and Thomas Richardson.

    He graduated in medicine from Washington University in St. Louis in 1976. He is currently Mitchell L. and Robin LaFoley Dong Professor of Epidemiology at Harvard T.H. Chan School of Public Health. He has published over 100 papers in academic journals and is an ISI highly cited researcher.

https://www.hsph.harvard.edu/profile/james-m-robins/ 

    C. F. Jeff Wu, Chinese University of Hong Kong, Shenzhen

    An internationally renowned statistician and member of the U.S. National Academy of Engineering, he is the Xueqin Chair Professor and Dean of the School of Data Science at the Chinese University of Hong Kong, Shenzhen. Previously, he served as the H.C. Carver Professor of Statistics at the University of Michigan, a Professor in the School of Industrial and Systems Engineering at the Georgia Institute of Technology, and the Coca-Cola Chair Professor of Statistics. In 2011, he received the R.A. Fisher Lectureship. In 1997, he was the first to coin the term "Data Science," advocating for renaming statistics to data science and referring to statisticians as data scientists.

    His primary research focuses on applied mathematical sciences (statistics) and engineering sciences (quality engineering and industrial engineering).

https://sds.cuhk.edu.cn/en/teacher/1900

Keynote speaker 6:

    Zhihua Zhou, Nanjing University

    An expert in artificial intelligence research, he is currently the Vice President of Nanjing University, Dean of the School of Computer Science at Nanjing University, and concurrently serves as Dean of the Nanjing University School of Artificial Intelligence. He is also the Executive Deputy Director of the State Key Laboratory for Novel Software Technology and Director of the Institute of Machine Learning and Data Mining. Additionally, he is a Fellow of the European Academy of Sciences.

    His primary research areas include artificial intelligence, machine learning, and data mining.

https://www.nju.edu.cn/info/1040/372961.htm