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 Alex Paskov. Operations Research. Forthcoming. Download Preprint.
Bertsimas, Dimitris, Ryan Cory-Wright, and Vassilis Digalakis. Manufacturing & Service Operations Management. Forthcoming. Supplemental Materials.
Gurnee, Wes, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, and Dimitris Bertsimas. Transactions in Machine Learning Research. Forthcoming.
Bertsimas, Dimitris, and Vassilis Digalakis. IEEE Transactions on Knowledge and Data Engineering. Forthcoming. Download Paper.
Bertsimas, Dimitris, and Jean Pauphilet. Management Science. Forthcoming. Supplementary Materials.
Maragno, Donato, Holly Wiberg, Dimitris Bertsimas, Ş. İlker Birbil, Dick den Hertog, and Adejuyigbe O. Fajemisin. Operations Research. Forthcoming. arXiv Preprint. Supplemental Materials.
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.
"For those private market investors willing to embrace external data, the rewards can be significant."Harvard Business Review
"AI will become the predominant methodology for predictions and decision-making across all fields."
"These tools provide crucial information for the management of water resources, allowing governments to prioritize their allocation."
"We present AI applications in unusual areas, with examples from the real world, in order to demonstrate that it is suitable everywhere."
The goal of business analytics is to determine which datasets are useful and how they can be leveraged to solve problems and increase efficiency, productivity, and revenue. In this non-technical online program, you will learn a practical framework that will enable you to use data to improve decision-making.
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.
