Dimitris Bertsimas


Dimitris Bertsimas


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 doctorla 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 and Jacquillat win Pierskalla Best Paper Award

INFORMS honors Bertsimas twice

Dimitris Bertsimas’s class is honored

Dimitris Bertsimas named Distinguished Lecturer

Dimitris Bertsimas receives 2016 Harold Larnder Prize

Bertsimas wins Jamieson Prize

Dimitris Bertsimas was awarded the 2008 Farkas Prize of the INFORMS Optimization Society


"A Practically Efficient Algorithm for Adaptive Distributionally Robust Linear Optimization Problems."

Bertsimas, Dimitris, Melvyn Sim, and Meilin Zhang. Management Science. Forthcoming.

"Balancing Efficiency and Fairness in Liver Transplant Access: Tradeoff Curves for the Assessment of Organ Distribution Policies."

Bertsimas, Dimitris, Theodore Papalexopoulos, Nikolaos Trichakis, Yuchen Wang, Ryutaro Hirose, Parsia Vagefi. Transplantation. Forthcoming. github Supplement.

"Certifiably Optimal Sparse Inverse Covariance Estimation."

Bertsimas, Dimitris, Jourdain Lamperski, and Jean Pauphilet. Mathematical Programming. Forthcoming.

"Data-driven Assortment Optimization."

Dimitris Bertsimas, and Velibor V. Mišić. Management Science. Forthcoming.

"Relative Robust and Adaptive Optimization."

Bertsimas, Dimitris, and Iain Dunning. INFORMS Journal of Computing. Forthcoming.

"Sparse Regression: Scalable Algorithms and Empirical Performance."

Bertsimas, Dimitris, Jean Pauphilet, and Bart Van Parys. Statistical Science. Forthcoming.

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Prof. Dimitris Bertsimas and nearly two dozen doctoral students are using machine learning and optimization to find answers and generating accurate real-time insight into the pandemic.

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