SPEAKER: Prof. Vijay Nair

ABSTRACT:

Traditional reliability analysis is based on time-to-failure data. In this talk, we discuss two different directions that lead to more informative reliability inference. The first is multi-state models. Challenges in statistical inference based on interval-censored data will be described, and methods for doing likelihood-based inference in semi-Markov models will be discussed. The second part of the talk will provide an overview of degradation models, describe a class of non-homogeneous Gaussian processes and some inference issues. This talk is based on joint work with current and former students Yang Yang and Xiao Wang.


Bio: Vijay Nair is the Donald A. Darling Professor of Statistics and Professor of Industrial and Operations Engineering at the University of Michigan, Ann Arbor. He has been Chair of the Department of Statistics sine 1998. Previously, he was a Research Scientist in the Mathematical Sciences and Operations Research Centers at Bell Laboratories for fifteen years.
His research interests include engineering statistics, information technology, quality and process improvement, industrial experiments, reliability and risk analysis, neuro-informatics, and statistical methods in behavioral intervention research. He also has extensive practical experience in the automotive, semiconductor, and telecommunications industries.
Vijay has a Bachelor’s degree in Economics from the University of Malaya (Malaysia) and a Ph. D. in Statistics from the University of California, Berkeley. He has been editor of Technometrtics, International Statistical Review, coordinating editor of the Journal of Statistical Planning and Inference, and has served on the editorial boards of many other leading statistics and quality journals. He is currently Vice President of the International Statistics Institute, President-elect of the International Society for Business and Industrial Statistics, and Chair of the Statistics Division of the American Society for Quality. He has chaired or co-chaired several panels of the National Academies and is a former chair of the Board of Trustees of the National Institute of Statistical Sciences. He is a Fellow of the American Association for the Advancement of Science, the American Statistical Association, the American Society for Quality, and the Institute of Mathematical Statistics.