Prof. Peter Glynn| Analytics, Data Science, and Simulation: Opportunities and Challenges

Biography of Speaker

Peter W. Glynn is the Thomas Ford Professor in the Department of Management Science and Engineering (MS&E) at Stanford University, and also holds a courtesy appointment in the Department of Electrical Engineering. He received his Ph.D. in Operations Research from Stanford University in 1982. He then joined the faculty of the University of Wisconsin at Madison, where he held a joint appointment between the Industrial Engineering Department and Mathematics Research Center, and courtesy appointments in Computer Science and Mathematics. In 1987, he returned to Stanford, where he joined the Department of Operations Research. From 1999 to 2005, he served as Deputy Chair of the Department of Management Science and Engineering, and was Director of Stanford's Institute for Computational and Mathematical Engineering from 2006 until 2010.

He served as Chair of MS&E from 2011 through 2015. He is a Fellow of INFORMS and a Fellow of the Institute of Mathematical Statistics, and was an IMS Medallion Lecturer in 1995 and INFORMS Markov Lecturer in 2014. He was co-winner of the Outstanding Publication Awards from the INFORMS Simulation Society in 1993, 2008, and 2016, was a co-winner of the Best (Biannual) Publication Award from the INFORMS Applied Probability in 2009, and was the co-winner of the John von Neumann Theory Prize from INFORMS in 2010. In 2012, he was elected to the National Academy of Engineering. He was Founding Editor-in-Chief of Stochastic Systems and is currently Editor-in-Chief of Journal of Applied Probability and Advances in Applied Probability. His research interests lie in simulation, computational probability, queueing theory, statistical inference for stochastic processes, and stochastic modeling.

Prof. Jim DAI, the Co-director and Professor of iDDA introduced Prof. Peter Glynn to the audiances.

Spotlights of Prof. Peter Glynn's Seminar Talk

Abstract |

Prof. Peter Glynn discussed research questions that were likely to become more important in the next decade, as data, modeling, and simulation became more tightly integrated within various decision platforms. Simulation could play a key role in improving decision-making, but the ways in which simulation would be used may require new research-based methodologies.

Inspiration|

Professor Glynn pointed out that machine learning has entered a golden era with the rapid development of the amount of data and the computing capacity. Meanwhile, the predicting and diagnosing models will be the future emphasis of Stochastic Modeling. Professor Glynn also noted that there were several limitations about the current methods of machine learning to train data. He presented some heated topics concerning the fields of stochastic ssimulation, machine learning and data science, such as the amnesic memory and numerical methods during non-stationary process, imitating non-observational status with Monte Carlo Method, combining machine learning and physics models as well as research opportunity regarding algorithm principles and computation.

After the talk，Prof. Yin Zhang, the Co-director and Professor of iDDA awarded a "Speaker of Master Forum" certificate to Prof. Peter Glynn on behalf of CUHK-Shenzhen.

Prof. Peter Glynn took a group photo with all professors and audiences.

For more information, please extract the QR code below and follow iDDA.

Co-author| Chrise Chen , student of 2017SME, CUHK-Shenzhen

Co-author| Yuchen Yang, visiting PhD student of Rice University