CityU IAS News
Modeling and Analysis of Markov Processes with Non-stationary Transition Probabilities
30 October 2018
Professor Peter Glynn, a recognized scholar in management science and the IAS Senior Fellow, delivered a lecture on 29 October for the Institute for Advanced Study (IAS) Distinguished Lecture Series: Frontiers in Operations Research / Operations Management at City University of Hong Kong (CityU).
Professor Glynn presented the latest research results about Markov Processes in his lecture titled “Modeling and Analysis of Markov Processes with Non-stationary Transition Probabilities”. He discussed equations that arise when applying Markov models to the study of time-varying systems. He also introduced some new limit theorems and approximations that can be applied to Markov processes having non-stationary transition probabilities. In the end, Professor Glynn featured a new class of numerical schemes for analyzing time-varying Markov chains.
The lecture was chaired by Professor Duan Li, School of Data Science, CityU. Two scholars in the field were invited to be discussants, namely Professor Jeff Hong, School of Management and School of Data Science, Fudan University, and Dr. Xiaowei Zhang, Department of Management Sciences, CityU. They provided a wide range of perspectives on the topic and the lecture was well received by the audience.
Professor Glynn is the Thomas Ford Professor in the Department of Management Science and Engineering (MS&E) at Stanford University. His research interests lie in simulation, computational probability, queueing theory, statistical inference for stochastic processes, and stochastic modeling. Professor Glynn is the recipient of many prestigious awards due to his contributions to the areas of operations research and management science. He is a Fellow of INFORMS, a Fellow of Institute of Mathematical Statistics and a member of the National Academy of Engineering; and the co-winner of the John von Neumann Theory Prize.
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