Rate My Professor John Chen

John Chen is Professor of Statistics in the Department of Mathematics and Statistics at Bowling Green State University. He earned his Ph.D. in Statistics from the University of Sydney in 1996, an M.A. in Statistics from the same university in 1993, an M.S. in Statistics from Zhongshan University in 1989, and a B.A. in Mathematics from Zhongshan University in 1986. Following his doctorate, he served as a postdoctoral fellow in Statistics at McMaster University from 1996 to 1998. Chen joined Bowling Green State University in 2000 as Assistant Professor, was promoted to Associate Professor in 2004, and to Professor in 2010. He has held visiting appointments, including Professor at the University of California, Berkeley in 2018 and at the University of Michigan in 2010, and Visiting Assistant Professor jointly in the Departments of Statistics and Psychiatry at the University of Pittsburgh from 1998 to 2000. His research focuses on probability, biostatistics, and data analysis. Chen has supervised multiple Ph.D. dissertations, including those on refined neural networks for time series predictions, methodologies for missing data with range regressions, and dose-response analysis for time-dependent efficacy.

Professor Chen has received the KME Teaching Excellence Award from Kappa Mu Epsilon at Bowling Green State University in 2004 and 2006. He earned Certificates of Appreciation from the Center for Faculty Excellence at BGSU in 2019, 2020, and 2021 for recognition by students at the Annual Teaching and Learning Summit. In recent years, he was selected for the Shanklin AI Innovation Award for his project on AI-Enhanced Teaching Materials for Statistics and Data Science and received funding through the President’s Innovation Fund for AI in Teaching and Learning, involving student contributions on topics such as missing data mechanisms, imputation methods, and hypothesis testing. Chen has served on research proposal review panels for the National Science Foundation and National Institutes of Health, acted as Graduate Coordinator for the department from 2007 to 2010, and contributed as a panelist and committee member. His scholarly work includes publications such as 'Simultaneous Confidence Regions and Weighted Hypotheses on Parameter Arrays' (2023), 'Weighted step-down confidence procedures with applications to gene expression data' (2020), 'Retrospective Analysis of Thromboelastography-Directed Transfusion in Isolated CABG' (2020), and 'Thrombelastography-Directed Transfusion in Cardiac Surgery' (2019), amassing over 850 citations. He chairs the department's colloquium committee and serves on editorial boards.