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.
https://business.cornell.edu/faculty-research/faculty/lc898/
Keynote speaker 3:
鄂维南,北京大学
国际知名数学家,中国科学院院士、北京大学讲席教授、大数据分析与应用技术国家工程实验室主任、北京大学国际机器学习研究中心主任、北京科学智能研究院院长、北京大数据研究院院长、中国工业与应用数学学会顾问、武汉数学与智能研究院学术委员会主任。曾任普林斯顿大学数学系和应用数学及计算数学研究所教授。
主要从事计算数学、应用数学、机器学习及其在力学、物理、化学和材料科学等领域中的应用等方面的研究。
https://www.math.pku.edu.cn/jsdw/js_20180628175159671361/e_20180628175159671361/138270.htm
Keynote speaker 4:
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/
Keynote speaker 5:
吴建福,香港中文大学(深圳)
国际知名统计学家、美国国家工程院院士,香港中文大学(深圳)数据科学学院校长学勤讲座教授。曾任密歇根大学H. C. Carver统计学讲座教授、佐治亚理工学院工业及系统工程系教授、可口可乐统计学讲座教授、2011年获得费雪讲座奖(R.A. Fisher Lectureship)。1997年首创数据科学(Data Science)这一术语,并主张将统计学改名为数据科学,将统计学家称为数据科学家。
主要从事应用数学科学(统计)、工程科学(质量工程及工业工程)方面的研究。
https://sds.cuhk.edu.cn/en/teacher/1900
Keynote speaker 6:
周志华,南京大学
人工智能研究专家,现任南京大学副校长、南京大学计算机学院院长,南京大学人工智能学院院长(兼),计算机软件新技术国家重点实验室常务副主任、机器学习与数据挖掘研究所所长,欧洲科学院院士。
主要从事人工智能、机器学习、数据挖掘等领域的研究工作。
https://www.nju.edu.cn/info/1040/372961.htm
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