Speaker
Dr. Subha Chakraborti, Professor of Statistics, Department of Information Systems, Statistics and Management Science, University of Alabama, Fellow of ASA, Elected Member of ISI
Title
Statistics Seminar Series
Subtitle
Statistical Process Monitoring: From Shewhart to the Age of AI
Physical Location
Allen 411
Abstract:
Statistical process monitoring (SPM) has evolved from Shewhart's simple control charts to a rich body of theory for detecting change in data streams. This talk traces that evolution: classical charts (Shewhart, CUSUM, EWMA) and their likelihood-ratio foundations; generalized likelihood ratio methods; distribution-free approaches that avoid restrictive assumptions; and the effect of estimated parameters on control chart performance, including recent work on cautious parameter learning. The talk also addresses change point detection, post-signal diagnostics, and touches on SPM, AI and Machine Learning-based anomaly detection, closing with some future directions.
About the Speaker:
Dr. Subhabrata ("Subha") Chakraborti is a Professor of Statistics in the Department of Information Systems, Statistics and Management Science at the Culverhouse College of Business, University of Alabama (UA), where he holds the Robert C. and Rosa P. Morrow Faculty Excellence Fellowship. A Fellow of the American Statistical Association and Elected Member of the International Statistical Institute, he is a two-time Fulbright Scholar and served as a SARCHI Tier I Visiting Professor at the University of Pretoria, South Africa. He has held additional visiting professorships in Brazil, the Netherlands, and France, and was named 2020 SEC Professor of the Year at UA. He earned his Ph.D. in Statistics from SUNY Buffalo.
Over a distinguished career, Professor Chakraborti has made lasting contributions to nonparametric inference, statistical process monitoring and control charts, changepoint analysis, and likelihood-based methods across distribution families, authoring more than 150 publications. He is co-author of two major books in the field: the classic Nonparametric Statistical Inference with J.D. Gibbons (Taylor and Francis) and Nonparametric Statistical Process Control with Marien Graham (Wiley). He has sustained a wide-ranging network of international collaborations with researchers in South Africa, Brazil, India, Greece, and Italy, and has chaired the dissertations of numerous Ph.D. students over the years.
Note:
Contact Prof. JZ at jzhang@math.msstate.edu for additional information.