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 system, energy systems, robotics, and management.
Frank Youhua Chen, Candace Arai Yano. Improving Supply Chain Performance and Managing Risk Under Weather-Related Demand Uncertainty”. Management Science.
Superhuman Performance of Surgical Tasks by Robots using Iterative Learning from Human-Guided Demonstrations
Superhuman Performance of Surgical Tasks by Robots using Iterative Learning from Human-Guided Demonstrations. Jur van den Berg, Stephen Miller, Daniel Duckworth, Humphrey Hu, Andrew Wan, Xiao-Yu Fu, Ken Goldberg, Pieter Abbeel. IEEE International Conference on Robotics and Automation (ICRA). Anchorage, AL. May 2010.
J.-H. Kim, H.-S. Ahn and R. Righter, “Optimal Production Policies with Multistage Stochastic Leadtimes,” Probability in the Engineering and Informational Sciences, vol. 23, pp. 515-543, 2009.
X. Guo, P. Kaminsky, P. Tomecek, and M. K. Yuen. Optimal spot market inventory strategy in the presence of cost and price risk, Mathematical Methods for Operations Research,73:109-137, 2011.
Alper Atamturk and Vishnu Narayanan. “Conic Mixed-Integer Rounding Cuts”. Mathematical Programming 122, 1-20, 2010. https://link.springer.com/article/10.1007%2Fs10107-008-0239-4.
X. Guo, R. Jarrow, and Y. Zeng. Credit risk models with incomplete information, (earlier version “Information reduction in credit risk models”,) Mathematics of Operations Research, 34(2): 320-332, 2009.