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
Dynamic pricing and matching in ride-hailing platforms
Yan, Chiwei & Zhu, Helin & Korolko, Nikita & Woodard, Dawn. (2019). Dynamic pricing and matching in ride‐hailing platforms. Naval Research Logistics (NRL). 67. 10.1002/nav.21872.
Randomized FIFO Mechanisms
Castro, F., Ma, H., Nazerzadeh, H., & Yan, C. (2021). Randomized FIFO Mechanisms. ArXiv. /abs/2111.10706
A Dynamic Model for Airline Fleeting and Scheduling
Yan, Chiwei & Ghate, Archis. (2022). A Dynamic Model for Airline Fleeting and Scheduling. SSRN Electronic Journal. 10.2139/ssrn.4197493.
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives
Freund, Robert & Grigas, Paul & Mazumder, Rahul. (2015). A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives. The Annals of Statistics. 45. 10.1214/16-AOS1505.
Joint Online Learning and Decision-making via Dual Mirror Descent
Lobos, Alfonso & Grigas, Paul & Wen, Zheng. (2021). Joint Online Learning and Decision-making via Dual Mirror Descent.
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.