Bayesian Nonparametrics for Causal Inference and Missing Data

Dr. Daniels received his undergraduate degree from Brown University in Applied Mathematics and doctoral degree from Harvard University in Biostatistics. He has been on the faculty at Iowa State and University of Texas at Austin.

Currently, Dr. Daniels is Professor, Andrew Banks Family Endowed Chair, and Chair in the Department of Statistics at the University of Florida. He is a past president of ENAR. He is a fellow of the American Statistical Association, past chair of the Statistics in Epidemiology Section of the American Statistical Association (ASA), former chair of the Biometrics Section of the ASA, and former editor of Biometrics.

He has received the Lagakos Distinguished Alumni Award from Harvard Biostatistics and the L. Adrienne Cupples Award from Boston University.

He has published extensively on Bayesian methods for missing data, longitudinal data and causal inference and has been funded by NIH R01 grants as PI and/or MPI since 2001. He also has a strong and productive record of collaborative research, with a focus on behavioral trials in smoking cessation and weight management, muscular dystrophy, and HIV.

Dr. Linero received his PhD in Statistics from the University of Florida. He is currently Assistant Professor in the Department of Statistics and Data Sciences at the University of Texas at Austin. His research is broadly focused on developing flexible Bayesian methods for complex longitudinal data, as well as developing tools for model selection, variable selection, and causal inference within the Bayesian nonparametric framework for high-dimensional problems.

Dr. Roy received his PhD in Biostatistics from the University of Michigan. He is currently Professor of Biostatistics and Chair of the Department of Biostatistics and Epidemiology at Rutgers School of Public Health. He directs the biostatistics core of the New Jersey Alliance for Clinical and Translational Science. He is a fellow of the American Statistical Association (ASA) and recipient of the Causality in Statistics Education Award from the ASA. His methodological research has focused on flexible Bayesian methods for causal inference. As a collaborative statistician, he has worked on studies in many areas of medicine and public health, including chronic kidney disease, hepatotoxicity of medications, and SARS-CoV-2.

Dr. Daniels博士在布朗大學獲得應用數學學士學位，並在哈佛大學獲得生物統計學博士學位。他曾在愛荷華州立大學和德克薩斯大學奧斯汀分校擔任教職。目前，Dr. Daniels博士是佛羅里達大學統計學系的教授、Andrew Banks家族捐贈的講座教授和系主任。他曾擔任ENAR的主席，是美國統計學會的會士，曾擔任美國統計學會流行病統計學部門的主席、生物計量學部門的主席和Biometrics的編輯。他曾獲得哈佛生物統計學系的Lagakos傑出校友獎和波士頓大學的L. Adrienne Cupples獎。他在貝葉斯方法應用於缺失數據、長期數據和因果推斷方面發表了大量論文，並自2001年以來一直以NIH R01資助的項目負責人和/或共同負責人的身份進行研究。他在合作研究方面也有豐富的成果，重點是在戒菸和體重管理、肌肉萎縮症和HIV方面的行為試驗。

Dr. Linero博士在佛羅里達大學獲得統計學博士學位，目前是德克薩斯大學奧斯汀分校統計與數據科學系的助理教授。他的研究主要集中在發展靈活的貝葉斯方法，應用於複雜的長期數據，以及在高維問題的貝葉斯非參數框架中開發模型選擇、變量選擇和因果推斷工具。

Dr. Roy博士在密歇根大學獲得生物統計學博士學位，目前是羅格斯公共衛生學院生物統計學和流行病學系的教授和系主任。他負責指導新澤西臨床和轉譯科學聯盟的生物統計核心。他是美國統計學會的會士，並獲得了美國統計學會頒發的統計教育中的因果關係獎。他的方法研究主要集中在靈活的貝葉斯方法應用於因果推斷。作為一名合作統計學家，他在許多醫學和公共衛生領域的研究中工作，包括慢性腎臟病、藥物的肝毒性和SARS-CoV-2。