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Data-driven Decision-making and Optimization: Formulations, Algorithms, and Applications

演讲者

Bismark Singh

时间

2026年04月30日 10:00 至 11:30

地点

A3-4-101

线上

Zoom 559 700 6085 (BIMSA)

摘要

Practically any real-world system requires discrete decision-making under uncertainty. Stochastic programming is a field of mathematics---at the the interface of statistics, computer science, and mathematical optimization---that defines the theory behind modeling risk for such decision-making. Here, reliable decisions must be taken before the uncertainty is revealed via discrete scenarios. However, such systems are computationally data-intensive and require tailored algorithmic approaches for their solution. This talk presents a vision of the future of interdisciplinary science and the vital role mathematical optimization will play in it. All presented materials are in the public domain.

演讲者介绍

Bismark Singh is an associate professor in operational research in the School of Mathematical Sciences at the University of Southampton, UK. He received a habilitation (2023) in mathematics from the Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany; PhD and MSc degrees in operations research from The University of Texas (UT) at Austin, US; and, a B.Tech. (2011) degree in chemical engineering from the Indian Institute of Technology (IIT) Delhi. Between 2016 and 2019 he held positions at Sandia National Laboratories, US in the Discrete Math & Optimization group. His research has been funded by agencies including the Deutsche Forschungsgemeinschaft (DFG), the Horizon 2020 program, the Bavarian State Ministry for Science and Art, and the US Department of Energy. He is a Senior Member of IEEE, a Fellow of Institute of Mathematics and its Applications, and an Associate Fellow of The OR Society. He is the Winner of the 2023 Mathematics Young Investigator Award. In 2024-25, he was a Distinguished Research Fellow at TU Dresden, Germany. For further information, visit: https://bissi1.github.io/.