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
Hybrid of fixed and mobile charging systems for electric vehicles: System design and analysis
Chengzhang, Wang & He, Fang & Shen, Max & Li, Meng. (2021). Hybrid of fixed and mobile charging systems for electric vehicles: System design and analysis. Transportation Research Part C: Emerging Technologies. 126. 103068. 10.1016/j.trc.2021.103068.
Assessment of battery utilization and energy consumption in the large-scale development of urban electric vehicles
Zhao, Yang & Wang, Zhenpo & Shen, Max & Sun, Fengchun. (2021). Assessment of battery utilization and energy consumption in the large-scale development of urban electric vehicles. Proceedings of the National Academy of Sciences. 118. e2017318118. 10.1073/pnas.2017318118.
Enhanced Modeling of Contingency Response in Security-constrained Optimal Power Flow
T. Altun, R. Madani, A. Atamtürk, R.Baldick, A. Davoudi. Enhanced Modeling of Contingency Response in Security-constrained Optimal Power Flow. BCOL Research Report 21.01, IEOR, University of California-Berkeley.
Mean–field moral hazard for optimal energy demand response management
Elie, Romuald & Hubert, Emma & Mastrolia, Thibaut & Possamaï, Dylan. (2019). Mean-field moral hazard for optimal energy demand response management.
Deep Learning Can Significantly Accelerate Grasp-Optimized Motion Planning
Deep Learning Can Significantly Accelerate Grasp-Optimized Motion Planning. Jeffrey Ichnowski, Yahav Avigal, Vishal Satish, Ken Goldberg. Science Robotics Journal. V5(48), 18 Nov 2020. [Paper] [Video].