Daniel Freund

Faculty

Daniel Freund

Support Staff

Get in Touch

Title

About

Academic Groups

Academic Area

Daniel Freund is the Class of 1947 Career Development Professor and an Assistant Professor of Operations Management at the MIT Sloan School of Management. 

His research focuses on complex decision-making problems in the sharing economy. During his PhD he developed the analytical methods used by bike-sharing systems like Citi Bike, Ford Go Bike, and Boston Blue Bikes to inform their rebalancing, thus enabling thousands of incremental bike rides every day. Prior to joining MIT, Daniel spent a year as a Research Fellow at Lyft Marketplace Labs where he developed new algorithms and market mechanisms for the ride sharing industry. 

He received the 2021 APS Best Publication Award, the 2018 George B. Dantzig Dissertation Award, the 2018 Daniel H. Wagner Prize for Excellence in Operations Research, and a Best Paper Award at the 2018 ACM SIGCAS Conference. He was also a finalist for the 2017 George Nicholson student paper prize, the 2018 POM Applied Research Challenge, and the 2020 Daniel H. Wagner Prize.

Freund 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 Prof. David B. Shmoys.

Publications

"Overbooking with Bounded Loss."

Freund, Daniel and Jiayu Zhao. Mathematics of Operations Research Vol. 48, No. 3 (2023): 1344-1363. Supplemental Materials. Download Preprint.

"Minimizing Multimodular Functions and Allocating Capacity in Bike‐Sharing Systems."

Freund, Daniel, Shane G. Henderson, and David B. Shmoys. Operations Research Vol. 70, No. 5 (2022): 2715-2731. Download Preprint. Supplemental Materials.

"Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework."

Banerjee, Siddhartha, Daniel Freund, and Thodoris Lykouris. Operations Research Vol. 73, No. 3 (2022): 1783-1805. arXiv Preprint.

"Fair Incentives for Repeated Engagement."

Freund, Daniel and Chamsi Hssaine, MIT Sloan Working Paper 6442-21. Cambridge, MA: MIT Sloan School of Management, October 2021.

Load More

Recent Insights

Ideas Made to Matter

How to build an effective analytics practice

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.

Read Article

Media Highlights