Scholar
Sai Srivatsa Ravindranath
Google Scholar ID: dKJ9ca4AAAAJ
Harvard University
Citations & Impact
Citations
570
H-index
8
i10-index
8
Publications
14
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Published papers: 'Optimal Auctions through Deep Learning: Advances in Differentiable Economics' (Journal of the ACM, 2023), 'Data Market Design through Deep Learning' (NeurIPS, 2023), 'Deep Learning for Two-Sided Matching' (MATCH-UP Workshop, 2022), etc.
Research Experience
- Spent two years as a Student Researcher at Google Research, collaborating with the Algorithms and Optimization Team in NYC on topics at the intersection of mechanism design and LLMs, and with the Market Algorithms team in Mountain View on Auctions and Reinforcement Learning. Before that, was a Research Fellow at Microsoft Research, India, with the Machine Learning and Optimization group.
Education
- PhD candidate in Computer Science at Harvard University, advised by Prof. David Parkes; B.Tech in Electrical Engineering with a minor in Computer Science from the Indian Institute of Technology, Kharagpur.
Background
- Research interests include Deep Learning, Algorithmic Economics, and Multi-Agent Systems. Focuses on how learning-based methods can be applied to problems in algorithmic design, particularly in settings involving strategic agents.
Miscellany
- Recently exploring projects at the intersection of LLMs and multi-agent systems, with a focus on what market design looks like when LLMs act as economic agents.
Co-authors