David Bergman

Associate Dean for Faculty and Research
Professor

Operations and Information Management

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David Bergman is a leading scholar and educator in business analytics, operations research, and data-driven decision making at the University of Connecticut School of Business.

He currently serves as Associate Dean for Faculty and Research at the School of Business, as the Provost’s Special Advisor on Artificial Intelligence, and as a faculty member in the Operations and Information Management (OPIM) department.

His academic work focuses on large-scale automated decision-making, machine learning, discrete optimization, integer programming, and the integration of advanced analytics techniques to solve complex business challenges. His work has appeared in leading journals including Operations Research, Management Science, INFORMS Journal on Computing, Production and Operations Management, Decision Support Systems, Constraints, and Journal of Artificial Intelligence Research.

Bergman earned his Ph.D. and M.S. in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University, along with additional graduate and undergraduate degrees in mathematics and statistics from Stony Brook University.

His research has been applied across a wide range of industries, including business analytics, operations management, sports analytics, military scheduling, and financial strategy. He is also a Certified Analytics Professional (CAP), reflecting his expertise in translating quantitative methods into practical business solutions.

Bergman teaches graduate-level courses in business process modeling, data management, statistics, optimization, and analytics. He enjoys helping students understand how data-driven decision-making can create measurable value in real-world settings. He is a recipient of the UConn School of Business Research Award, the UConn-AAUP Teaching Excellence Early Career Award, and the ACP Doctoral Research Award.

He has served as President of the Association for Constraint Programming and currently serves as Associate Editor for INFORMS Journal on Computing and on the Editorial Board of Constraints.

Education/Professional Certification

Ph.D., 2013, Carnegie Mellon University; M.S., 2010, Carnegie Mellon University; M.S., 2008, Stony Brook University; B.S., 2007, Stony Brook University.

Areas of Expertise and Interest

Large-scale automated decision making, decision diagrams, discrete optimization, integer programming, machine learning, integration of optimization techniques

Current Classes

OPIM 5272 – Business Process Modeling and Data Management

OPIM 5603 – Statistics in Business Analytics

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