Research
IEOR researchers investigate the latest mathematical tools, approaches, and methodologies to make new theoretical discoveries and innovations that touch nearly every industry, making them more efficient and profitable in areas such as supply chain, logistics, manufacturing, data science, energy systems, robotics, and management.
Selected Publications
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method
Liu, Heyuan & Grigas, Paul. (2021). Risk Bounds and Calibration for a Smart Predict-then-Optimize Method.
Smart “Predict, then Optimize”
Elmachtoub, Adam & Grigas, Paul. (2017). Smart “Predict, then Optimize”. Management Science. 68. 10.1287/mnsc.2020.3922.
Generalization Bounds in the Predict-then-Optimize Framework
El Balghiti, Othman & Elmachtoub, Adam & Grigas, Paul & Tewari, Ambuj. (2019). Generalization Bounds in the Predict-then-Optimize Framework.
Equilibria and incentives for illiquid auction markets
Derchu, Joffrey & Kavvathas, Dimitrios & Mastrolia, Thibaut & Rosenbaum, Mathieu. (2023). Equilibria and incentives for illiquid auction markets.
Asymptotically Optimal Competitive Ratio for Online Allocation of Reusable Resources
Goyal, V., Iyengar, G., & Udwani, R. (2020). Asymptotically Optimal Competitive Ratio for Online Allocation of Reusable Resources.
Periodic Reranking for Online Matching of Reusable Resources
Udwani, Rajan. (2022). Periodic Reranking for Online Matching of Reusable Resources. 966-966. 10.1145/3490486.3538344.