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Daniel Bienstock is the Liu Family Professor at the Data Science Institute, Columbia University, specializing in Industrial Engineering and Operations Research. He obtained his Ph.D. in Operations Research from MIT in 1985. Bienstock has held notable positions, including research roles at Bell Communications Research and as an assistant professor at Carnegie Mellon University. His research interests prominently feature optimization, with a special focus on discrete nonconvex optimization and the theory of high-performance implementation. Recent work has involved modeling cascading failures in power grids and the social impact of epidemics. He is the author of the book 'Potential Function Methods for Solving Linear Programming Problems: Theory and Practice', published in 2002 by Springer. Bienstock has been recognized with the Presidential Young Investigator Award in 1990 and has served as a plenary speaker at significant conferences, including the 2005 SIAM Conference on Optimization and the 2006 International Symposium on Mathematical Programming.
Columbia University • New York, NY
Liu Family Professor at the Data Science Institute, researching optimization and operations research.
Carnegie Mellon University • Pittsburgh, PA
Assistant professor at the Graduate School of Industrial Administration.
Department of Anthropology (GSAS)