Email: fsusan (at) mit (dot) edu
I am a fifth-year Ph.D student in the Operations Research Center at MIT, where I am advised by Prof. Negin Golrezaei. My research interests lie in the areas of machine learning, combinatorial algorithms, approximation algorithms, and mechanism design with applications to revenue management and online markets. I completed my undergraduate studies at MIT in 2018 with an SB in Mathematics and Electrical Engineering and Computer Science. During my studies, I have had the opportunity to intern at several companies including Meta, Twitter, Goldman Sachs, and Traveloka.
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization
- with Rad Niazadeh, Negin Golrezaei, Joshua Wang, and Ashwinkumar Badanidiyuru
- Management Science, 2022. A preliminary version appeared in the Proceedings of the 22nd ACM Conference on Economics and Computation (EC'21), 2021.
Active Learning for Non-Parametric Choice Models
- with Negin Golrezaei, Ehsan Emamjomeh-Zadeh, and David Kempe
- Under review for INFORMS Operations Research Journal, 2022. Presented at the 2022 INFORMS Annual Meeting and the 2022 INFORMS Revenue Management and Pricing Conference.
Fair Assortment Planning
- with Qinyi Chen, Negin Golrezaei, and Edy Baskoro
- Working paper. Presented at the 2022 MSOM Service SIG Conference and the 2022 INFORMS Revenue Management and Pricing Conference.
Multi-Platform Budget Management in Ad Markets with Non-IC Auctions
- with Negin Golrezaei and Okke Schrijvers
- Working paper.
SCRAM: Securely Measuring Cyber Risk
- with Leo de Castro, Andrew W. Lo, Taylor Reynolds, Vinod Vaikuntanathan, Daniel Weitzner, and Nicolas Zhang
- in Harvard Data Science Review, 2020