Hamed Rahimian
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Assistant Professor |
About me
I am currently an Assistant Professor in the Department of Industrial Engineering at Clemson University. Before joining Clemson IE, I was a Postdoctoral Research Fellow in the Department of Industrial Engineering and Management Sciences at Northwestern University. I received my Ph.D. in Industrial and Systems Engineering from the Department of Integrated Systems Engineering at The Ohio State University. I also received my M.Sc. in Industrial Engineering from The University of Arizona in 2012, and my M.Sc. and B.Sc. in Industrial Engineering from Sharif University of Technology, Tehran, Iran, in 2011 and 2008. My research has been recognized with several awards, including Runner-Up prize INFORMS Computing Society Student Paper Award (2017), 2nd Place prize in IISE Pristker Doctoral Dissertation Award (2019), and the Harold W. Kuhn Award (2022).
Research
My research focuses on data-driven decision-making and learning problems in uncertain and risky environments involving contextual data to develop robust and computationally efficient methodolody with theoretical gunarantees. In particular, my research interests include
Stochastic optimization
Data-driven optimization
Risk-averse and distributionally robust optimization Find out more.
News
October 2024: Our paper on “Ranking & Contextual Selection” is published in Operations Research.
September 2024: Our paper on “A Disjunctive Cutting Plane Algorithm for Bilinear Programming” is published in SIAM Journal of Optimization.
August 2024: I received a grant from Air Force Office of Scientific Research on ‘‘Multistage Stochastic Programs with Dynamic Learning."
July 2024: Presented a talk on “Multistage Chance-constrained Programming” at ISMP 2024, Montreal, Canada.
June 2024: Our paper on “Value of Risk Aversion in Perishable Products Supply Chain Management” is published in Computational Optimization and Applications.
March 2024: Appointed as Committee Member of 2024 INFORMS Computing Society Student Paper Award.
March 2024: Appointed as Associate Editor of INFORMS Journal on Computing.
March 2024: Honored to receive a Mathematical Programming 2023 Meritorious Service Award.
August 2023: Our paper on “Data-Driven Approximation of Contextual Chance-Constrained Stochastic Programs” is published in SIAM Journal of Optimization.
July 2023: Organized a minisymposium on “Recent Advances to Solve Stochastic and Robust Optimization Problems” at 2023 XVI International Conference Stochastic Programming.
April 2023: Our paper on “A Model of Supply-Chain Decisions for Resource Sharing with an Application to Ventilator Allocation to Combat COVID-19” is awarded the “Harold W. Kuhn Award” by the Journal of Naval Research Logistics.
October 2022: Presented a talk on “Contextual Expected-Value-Constrained Stochastic Programming” at INFORMS Annual Meeting 2022, Indianapolis, IN.
October 2022: Organized two sessions on “Distributionally Robust Learning and Optimization” at INFORMS Annual Meeting 2022, Indianapolis, IN.
October 2022: Submitted a journal paper on “Data-Driven Approximation of Contextual Chance-Constrained Stochastic Programs”.
July 2022: Our paper on “Frameworks and Results in Distributionally Robust Optimization” is published in Open Journal of Mathematical Optimization.
July 2022: Presented a talk on “Sequential Convexification of a Bilinear Set” at ICCOPT 2022, Lehigh, PA.
June 2022: Presented a talk on “Joint Stocking and Pricing Decisions for Distributionally Robust Inventory Problems with Decision-Dependent Demands” at ESCO-CMS 2022, Venice, Italy.
June 2022: Organized the Cluster of Optimization under Uncertainty at 2022 CORSINFORMS International Conference, Vancouver, Canada.
May 2022: Our paper on “A Synthetic Data-plus-Features Driven Approach for Portfolio Optimization” is published online in Computational Economics.
March 2022: Our paper on “Effective Scenarios in Multistage Distributionally Robust Optimization with a Focus on Total Variation Distance” is published in SIAM Journal on Optimization.
March 2022: Presented a talk on “Risk-Averse and Chance-Constrained Two-Stage Stochastic Programming Approach for Pharmaceutical Supply Chain Planning” at IOS 2022, Greenville, SC.
Aug 2020: Joined Clemson University as an Assistant Professor of Industrial Engineering.