Dorit S. Hochbaum is a Chancellor's full professor at UC Berkeley, in Industrial Engineering and Operations Research (IEOR). Hochbaum holds a PhD from the Wharton School of Business at the University of Pennsylvania. Prior to joining UC Berkeley in 1981, she held a faculty position at Carnegie Mellon University's GSIA. Her research interests are in the areas of discrete optimization, network flow techniques, data mining, image segmentation, supply chain management, and efficient utilization of resources. She has done work on approximation algorithms, location problems, movement of robots, routing and distribution problems, feasibility of VLSI designs, distribution of databases on computer networks, clustering problems, and medical imaging, among others. She has contributed to the analysis of heuristics and approximation algorithms in the worst case and on the average, and to the complexity analysis of algorithms in general, and of nonlinear optimization algorithms in particular. Her recent applications work is on problems related to homeland security, with flow-based pattern recognition algorithms; analyzing gene expression databases; scheduling and testing; production planning and supply chain streamlining for high tech industries and logistics; and planning problems in various industries. Her recent theoretical work focuses on particularly efficient techniques using network flow for data mining and image segmentation and for inverse problems, with applications varying from medical prognosis, error correction, medical imaging, nuclear threat detection, financial risk assessment and prediction, to group rankings and decision problems.
Hochbaum served as the chair of the Manufacturing and Information Technology group at the Haas School of Business. She is the founder and director of the UC Berkeley Supply Chain Initiative. She is the founder and co-director of the RIOT project.
Hochbaum is the author of over 150 papers that have appeared in the Operations Research, Management Science and Theoretical Computer Science literature. She has served as department editor for the Management Science department of Optimization and Modeling, and has served on a number of editorial boards.
Hochbaum was granted an honorary doctorate of sciences from the University of Copenhagen in 2004, for her work on approximation algorithms. In 2005, she was conferred the title of INFORMS fellow. She was appointed the Pinhas Naor lecturer at the Technion for 2013, and a Research Excellence professor at the University of Vienna in 2007. She is the winner of the 2011 INFORMS Computing Society prize for her work on algorithms for image segmentation. She was named a SIAM (Society of Industrial and Applied Mathematics) fellow in 2014.
- The Brain and Computation, Spring 2018. Visiting Scientist.
- Bridging Continuous and Discrete Optimization, Fall 2017. Visiting Scientist and Program Organizer.
- Algorithmic Spectral Graph Theory, Fall 2014. Visiting Scientist.
- Theoretical Foundations of Big Data Analysis, Fall 2013. Visiting Scientist.