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Xian Yu

Assistant Professor

Department of Integrated Systems Engineering

The Ohio State University

1971 Neil Ave, Columbus, OH 43210

Email: yu.3610@osu.edu

[Curriculum Vitae]

[Google Scholar]

Hi, I’m Xian Yu (于弦 in Chinese). I joined the Department of Integrated Systems Engineering at The Ohio State University as an Assistant Professor in August 2022. I completed my Ph.D. in Operations Research at the University of Michigan in April 2022, where I was advised by Prof. Siqian Shen. My research interests are in large-scale sequential decision-making and optimization under uncertainty, where my research focuses on utilizing special problem structures and deriving efficient algorithms for solving related problems arising in smart transportation, logistics, and supply chain management.

[Fully-Funded Ph.D. Positions] I am looking for self-motivated Ph.D. students with strong mathematical backgrounds and interests in (1) integrated learning and optimization or (2) distributional reinforcement learning.

Recent News

  • 10/2024, our paper titled “On the Value of Risk-Averse Multistage Stochastic Programming in Capacity Planning” is accepted by and will appear in INFORMS Journal on Computing.

  • 03/2024, Dr. Beste Basciftci and Dr. Xian Yu have co-organized two sessions at the INFORMS Optimization Society Conference 2024 on “Multi-stage Stochastic Programs” and “Recent Advancements on Optimization under Decision-Dependent Uncertainty”. 

  • 01/2024, new PhD student Minheng Xiao joined our group. Welcome, Minheng!

  • 10/2023, our group was invited to present at the INFORMS Annual Meeting in Phoenix, Arizona.

  • 10/2023, Dr. Yu received an NSF award on “Collaborative Research: SLES: Safe Distributional-Reinforcement Learning-Enabled Systems: Theories, Algorithms and Experiments“, in collaboration with University of Michigan (lead institution) and Arizona State University! [News]

  • 07/2023, Dr. Yu attended the International Conference on Stochastic Programming (ICSP) in Davis, California and gave a talk on “On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures”.

  • 07/2023, our paper titled “On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures” was accepted in the 40th International Conference on Machine Learning (ICML 2023), Honolulu, Hawaii. This is a joint work with Dr. Lei Ying from EECS at the University of Michigan.

  • 05/2023, Dr. Yu attended the SIAM Conference on Optimization in Seattle, Washington and gave a talk on “On the Value of Risk-Averse Multistage Stochastic Programming in Capacity Planning”.

  • 04/2023, our paper “Optimization and Decentralized Algorithms for Traffic Signal Control under Uncertain Travel Demand and Vehicle Turning Ratio” has been accepted in European Journal of Operational Research.

  • 03/2023, Dr. Yu won First Place in the IISE Pritsker Doctoral Dissertation Award for her dissertation titled “Sequential Optimization Under Uncertainty: Models, Algorithms, and Applications”. The award recognizes outstanding doctoral dissertation research in industrial engineering.

  • 01/2023, new PhD students Qing (Zoey) Zhu and Huangrong Sun joined our research group. Welcome, Zoey and Huangrong!

  • 10/2022, Dr. Yu attended the INFORMS Annual Meeting in Indianapolis, Indiana and gave a talk on “On the Value of Multistage Risk-Averse Stochastic Facility Location with or without Prioritization”.

  • 07/2022, Dr. Yu attended the seventh International Conference on Continuous Optimization (ICCOPT) conference at Lehigh University in Bethlehem, Pennsylvania, and gave a talk on “On the Value of Multistage Risk-Averse Stochastic Facility Location with or without Prioritization”.

  • 07/2022, Dr. Yu gave an invited talk on “Multistage Distributionally Robust Mixed-Integer Programming with Decision-Dependent Moment-Based Ambiguity Sets” in the Applied Analytics Lab at Carnegie Mellon University. Thanks for the invitation!