Faculty
Dimitris Bertsimas is the Boeing Leaders for Global Operations Professor of Management, a Professor of Operations Research, and the Associate Dean for the Master of Business Analytics at MIT.
A faculty member since 1988, his research interests include optimization, stochastic systems, machine learning, and their application. In recent years, he has worked in robust optimization, statistics, healthcare, transportation and finance. Bertsimas was a cofounder of Dynamic Ideas, LLC, which developed portfolio management tools for asset management. In 2002, the assets of Dynamic Ideas were sold to American Express. He is also the founder of Dynamic Ideas Press, a publisher of scientific books, the cofounder of Benefits Science, a company that designs health care plans for companies, of Dynamic Ideas Financial, a company that provides financial advice to customers, of Alpha Dynamics, an asset management company, P2 Analytics, an analytics consulting company and of MyA health, a personalized health care advice company.
Bertsimas has coauthored more than 200 scientific papers and the following books: Introduction to Linear Optimization (with J. Tsitsiklis, Athena Scientific and Dynamic Ideas, 2008); Data, Models, and Decisions (with R. Freund, Dynamic Ideas, 2004); Optimization over Integers (with R. Weismantel, Dynamic Ideas, 2005); and The Analytics Edge (with A. O'Hair andW. Pulleyblank, Dynamic Ideas, 2016). He is former department editor of Optimization for Management Science and of Operations Research in Financial Engineering. Bertsimas has supervised 59 doctoral and 31 Master students. He is currently supervising 22 doctoral students. A member of the National Academy of Engineering and an INFORMS fellow, he has received numerous research awards, including the Harold Larnder Prize (2016), the Philip Morse Lecturship prize (2013), the William Pierskalla best paper award in health care (2013), best paper award in Trapsoration (2013), the Farkas Prize (2008), the Erlang Prize (1996), the SIAM Prize in Optimization (1996), the Bodossaki Prize (1998), and the Presidential Young Investigator Award (1991–1996). He has also received recognition for his educational contributions: The Jamieson prize (2013) and the Samuel M. Seegal prize (1999).
Bertsimas holds a BS in electrical engineering and computer science from the National Technical University of Athens, Greece, as well as an MS in operations research and a PhD in applied mathematics and operations research from MIT.
Bertsimas, Dimitris, and Ryan Cory-Wright. INFORMS Journal of Computing. Forthcoming. Supplemental Material. arXiv Preprint.
Trichakis, Nikolaos, Theodore Papalexopoulos, Dimitris Bertsimas, James Alcorn, R.R. Goff, and D.E. Stewart. INFORMS Journal on Applied Analytics. Forthcoming.
Bertsimas, Dimitris, Bart P.G. Van Parys. Mathematical Programming: 1-40. Forthcoming.
Andrianesis, Panagiotis, Dimitris Bertsimas, Michael C. Caramanis, and William W. Hogan. IEEE Transactions on Power Systems. Forthcoming. arXiv Preprint.
Bertsimas, Dimitris, Alison Rose Ann Borenstein, Antonin Dauvin, and Agni Orfanoudaki. Naval Research Logistics. Forthcoming.
Bertsimas, Dimitris, and Vassilis Digalakis. IEEE Transactions on Knowledge and Data Engineering. Forthcoming. Download Paper.
Dimitris Bertsimas and Nikolaos Trichakis modeled a points-based framework called continuous distribution (CD) based on AI and machine learning to aid in allocating lung transplants.
A framework based on data, models, decisions, and value can help you leverage analytics for better business outcomes.
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A pair of MIT researchers recently set out to find the optimal starting word for the popular online puzzle.
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Over the course of six weeks, dive into the existing and potential applications of AI and ML in the pharmaceutical and biotech industry. Guided by expert MIT faculty, you’ll gain insight into the optimal AI tools for this industry and explore how they can be leveraged for early drug discovery.
In Artificial Intelligence in Health Care, the MIT Sloan School of Management and the MIT J-Clinic aim to equip health care leaders with a grounded understanding of the potential for AI innovations in the health care industry. The course explores types of AI technology, its applications, limitations, and industry opportunities.
