Ideas Made to Matter
8 steps to a stronger cybersecurity strategy
Use this framework to limit operational damage and monetary losses.
Nov 7, 2018
Fazel-Zarandi and Barnett win best paper award
December 18, 2024
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Mohammad Mehdi Fazel Zarandi
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Mohammad Fazel‐Zarandi is a Senior Lecturer at the MIT Sloan School of Management. His research interests are in the areas of data-driven decision-making and machine learning, with applications in public policy. His current research focuses on the use of analytics to analyze and improve decision-making in the public policy domain. Some of the topics he studies include immigration policy, criminal justice, and public health.
Mohammad's research has been published in flagship journals such as Operations Research and Management Science, and has been reported by the Los Angeles Times, the Boston Globe, the New York Times, the Washington Post, Bloomberg, and many other major media outlets.
He has taught various analytics courses to MBA and undergraduate students at MIT and has received multiple teaching awards, including the MIT Sloan Teacher of the Year in 2024, the Outstanding Teacher Award at the Sloan School of Management in 2023, and the MIT Graduate Teaching Award in the same year.
Before joining MIT, Mohammad was a Postdoctoral Associate and Lecturer at the Yale School of Management. He received his PhD from the Rotman School of Management, University of Toronto in Operations Management and his MS in Industrial Engineering, also from the University of Toronto.
Honors
Fazel-Zarandi named MIT Sloan School Teacher of the Year
May 8, 2024
Fazel-Zarandi wins Outstanding Teacher Award
May 12, 2023
Publications
"Why Did US Urban Homicide Spike in 2020? A Cross-Sectional Data Analysis for the Largest American Cities."
Fazel-Zarandi, Mohammad M. and Arnold Barnett. Risk Analysis Vol. 44, No. 7 (2024): 1616-1629.
"Can Firms Benefit from Competition?"
Fazel-Zarandi, Mohammad, Ignatius Horstmann, and Frank Mathewson. International Journal of Industrial Organization Vol. 76, (2021): 102740.
"Almost Robust Discrete Optimization."
Baron, Opher, Oded Berman, Mohammad M. Fazel-Zarandi, and Vahid Roshanaei. European Journal of Operational Research Vol. 276, No. 2 (2019): 451-465.
"Truthful Cheap Talk: Why Operational Flexibility May Lead to Truthful Communication."
Berman, Oded, Mohammad Fazel-Zarandi, and Dmitry Krass. Management Science Vol. 65, No. 4 (2019): 1624-1641.
"The Number of Undocumented Immigrants in the United States: Estimates Based on Demographic Modeling with Data from 1990-2016."
Fazel-Zarandi, Mohammad, Edward H. Kaplan, and Jonathan S. Feinstein. PLOS ONE Vol. 13, No. 9 (2018): e0201193.
"Approximating the First-Come, First-Served Stochastic Matching Model with Ohm's Law."
Fazel-Zarandi, Mohammad, and Edward H. Kaplan. Operations Reseach Vol. 66, No. 5 (2018): 1423-1432.
Recent Insights
Ideas Made to Matter
Undocumented immigrant population roughly double current estimate
New research shows the population could have been mismeasured for decades.
Sep 21, 2018
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