4 ways to use AI to improve lives, from MIT researchers
Artificial intelligence can tackle complex and important challenges, from creating fairer organ transplant policies to addressing asylum system backlogs.
Faculty
Daniel Freund is an Associate Professor of Operations Management at MIT Sloan.
His research applies techniques from optimization, stochastic modeling, and revenue management to problems in transportation, online platforms, and humanitarian immigration among others. His work has been widely recognized by INFORMS societies, including through the Service Science Responsible Research Paper Award (2024), the PSOR Best Paper Award (2nd place, 2024), the MSOM Best OM Paper in OR Award (2023), the Applied Probability Society Best Publication Award (2021), the George B. Dantzig Dissertation Award (2018), and the Daniel H. Wagner Prize for Excellence in Operations Research and Analytics (2018). Daniel is an AE for Operations Research, Mathematics of Operations Research, and Transportation Science.
Daniel holds a BSc in mathematics from the University of Warwick (UK), as well as an MS and a PhD in applied mathematics from Cornell University, where he was advised by David B. Shmoys. Before joining MIT, Daniel was a postdoc in Lyft's Marketplace Labs team.
Freund, Daniel and Wentao Wang. Manufacturing & Service Operations Management. Forthcoming. SSRN Version.
Freund, Daniel and Garrett van Ryzin. Transportation Research Part C: Emerging Technologies Vol. 181, (2025): 105314.
Daniel Freund, David Hausman, and Wentao Weng. In Proceedings of the 26th ACM Conference on Economics and Computation (EC'25), New York, NY: July 2025.
Freund, Daniel, Chamsi Hssaine, and Jiayu (Kamessi) Zhao, MIT Sloan Working Paper 7324-25. Cambridge, MA: MIT Sloan School of Management, June 2025.
Banerjee, Siddhartha, and Daniel Freund. Management Science Vol. 71, No. 6 (2025): 4877-4894. SSRN Preprint.
Freund, Daniel, Ilan Lobel, and Jiayu (Kamessi) Zhao. Manufacturing & Service Operations Management Vol. 28, No. 2 (2025): 496-516. SSRN Preprint. Supplemental Material.
Artificial intelligence can tackle complex and important challenges, from creating fairer organ transplant policies to addressing asylum system backlogs.
From designing intelligent decision processes to tapping the full power of deep learning, here are data practices to adopt now from MIT Sloan analytics faculty.
Rather than saying "we're going to use surge pricing at peak demand periods," they could offer discounts during off-peak periods.