Retsef Levi
· J. Spencer Standish (1945) Professor of ManagementMassachusetts Institute of Technology · Operations Management
Active 1972–2026
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About
Retsef Levi is the J. Spencer Standish (1945) Professor of Operations Management at the MIT Sloan School of Management. He is a member of the Operations Management Group at MIT Sloan and affiliated with the MIT Operations Research Center. Levi also serves as the faculty leader for Food Chain Supply Analytics. His research focuses on designing analytical data-driven decision support models and tools that address complex business and system design decisions under uncertainty, particularly in health and healthcare management, supply chain, procurement, inventory management, revenue management, pricing optimization, and logistics. Levi has led several industry-based collaborative research efforts with major academic hospitals and organizations across the U.S., including the FDA, Walmart Foundation, and various healthcare and food safety institutions. He has received numerous awards for his contributions, including the NSF Faculty Early Career Development award, the INFORMS Optimization Prize for Young Researchers, the Daniel H. Wagner Prize, and the Harold W. Kuhn Award. Levi teaches courses on operations management, analytics, risk management, system thinking, and healthcare, engaging students from various programs and industry partners. He has graduated multiple PhD, Master, and postdoctoral students and has been recognized for his teaching excellence.
Research topics
- Computer Science
- Business
- Artificial Intelligence
- Econometrics
- Machine Learning
- Economics
- Medicine
- Political Science
- Actuarial science
- Operations research
Selected publications
Proceedings of the National Academy of Sciences · 2022 · 311 citations
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hu…
The United States COVID-19 Forecast Hub dataset
Scientific Data · 2022 · 126 citations
Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hosp…
Assortment Optimization Under Consider-Then-Choose Choice Models
Management Science · 2020 · 92 citations
Consider-then-choose models, borne out by empirical literature in marketing and psychology, explain that customers choose among alternatives in two phases, by first screening products to decide which alternatives to consider and then ranking them. In this paper, we develop a dynamic programming framework to study the computational aspects of assortment optimization under consider-then-choose premises. Although nonparametric choice models generally lead to computationally intractable assortment o…
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
medRxiv (Cold Spring Harbor Laboratory) · 2021 · 77 citations
Abstract Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Fo…
Care coordination for healthcare referrals under a shared‐savings program
Production and Operations Management · 2022 · 19 citations
Accountable care organizations (ACOs) are responsible for the quality and cost of care of specified patient populations, including the cost of referrals. Motivated by this environment, we study care coordination for healthcare referrals. We consider an ACO that refers an uncertain number of patients from its attributed population to a preferred external provider for specialized health services. ACOs are typically paid under the Medicare Shared Savings Program (MSSP). Under the MSSP, the payer se…
Recent grants
NSF · $300k · 2015–2019
NSF · $400k · 2009–2015
NSF · $172k · 2007–2010
Frequent coauthors
- 35 shared
Peter F. Dunn
Harvard University
- 18 shared
David B. Shmoys
Cornell University
- 18 shared
Georgia Perakis
- 16 shared
Jonathan P. Wanderer
Vanderbilt University Medical Center
- 16 shared
J Standish
Vanderbilt University
- 16 shared
Brett A. Simon
- 16 shared
Bethany Daily
Massachusetts General Hospital
- 14 shared
Yanchong Zheng
Labs
Awards & honors
- NSF Faculty Early Career Development award
- INFORMS Optimization Prize for Young Researchers (2008)
- Daniel H. Wagner Prize (2013)
- Harold W. Kuhn Award (2016)
- MSOM Responsible Research in Operations Management award (20…
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