I am a Ph.D. Candidate in Machine Learning at Georgia Tech, advised by Prof. Juba Ziani
I’m passionate about about models that make effective sequential decisions, are fair across subpopulations, and preserve user privacy.
My research focus is:
- Recommender systems, especially generative retrieval and ranking
- Algorithmic fairness and differential privacy
Check out my publications and writings for more.
During my PhD, I've interned as an Applied Scientist at Amazon and as a ML engineer at Keysight.
Recent News
- Upcoming: This summer, I’ll be joining Pinterest as a ML Intern, working on generative retrieval.
- Feb 2025: Our paper,Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems has been accepted at TMLR 2025!
- Jan 2025: Our work,Improving Minimax Group Fairness in Sequential Recommendation is accepted at ECIR 2025. This is work I led during my internship at Amazon.
Experience
- Applied Scientist Intern, Amazon — Shopping Personalization (Fall 2024)
- Machine Learning Intern, Keysight — ML Explainability (Summer 2023)
- Research Intern, LIG — Fair Ad Auctions (Spring 2020)
Education
- Ph.D. in Machine Learning, Georgia Institute of Technology
Sep 2021 - April 2026
- Master's in Computer Science, École Normale Supérieure de Lyon, France
Sep 2019 - Aug 2020
- B.E. in Computer Science, BITS-Goa, India
Aug 2015 - Dec 2018
Awards
- Kiplinger Fellowship (Fall 2021, Spring 2022)
- University of Lyon Scholarship of Excellence (Fall 2019, Spring 2020)
- Merit Scholar, BITS Pilani (2015, 2016)
Teaching
- TA, ISyE 4803: Online Learning and Decision Making (Spring 2024)
- TA, ISyE 2027: Probability with Applications (Spring 2022)
- TA, ISyE 3133: Engineering Optimization (Fall 2021)
Academic Service
Reviewer: ICML, AAAI, ICLR, KDD, NeurIPS.