Rama Krishnamurthy

(First name pronunciation)

PhD student,
Courant Institute of Mathematical Sciences,
New York University.

Email- rk4312@nyu.edu

About Me

News

Welcome!
I am a PhD student at Courant Institute of Mathematical Sciences @ New York University since Fall 2022, advised by Prof. Lakshmi Subramanian. I was a Visiting Researcher at Meta in the FAIR team (2023-2025) mentored by Max Nickel.

Earlier, I was an M. Tech (by Research) student at the Dept. of Computer Science & Automation (CSA) at the Indian Institute of Science (IISc), Bangalore, where I am happy to have been advised by Prof. Rahul Saladi and also to have collaborated with Prof. Siddharth Barman and Prof. Aditya Gopalan.

My research interests broadly lie in the Machine Learning fields of Online Learning, Bandits, Game Theory, and Reinforcement Learning. My research problems are usually motivated by applications in Recommender Systems.

[Oct 2025] - Presenting our work on 'Creator Incentives in Recommender Systems' at INFORMS Annual Meeting in Atlanta GA!
[Aug 2025] - Presented our work on "On Slowly-varying Non-stationary Bandits" at RLC 2025 in Edmonton, Canada.
[July 2024] - Presented our work on "Collaborative Learning under Strategic Behavior: Mechanisms for Eliciting Feedback in Principal-Agent Bandit Games" [Open Review] at the Agentic Markets Workshop at ICML 2024 in Vienna.

Publications

On Slowly-varying Non-stationary Bandits
Ramakrishnan Krishnamurthy and Aditya Gopalan
at 2nd Reinforcement Learning Conference, RLC-2025 [OpenReview] [arXiv]
Optimal Algorithms for Range Searching over Multi-Armed Bandits
Siddharth Barman, Ramakrishnan Krishnamurthy, and Saladi Rahul
at 30th International Joint Conference on Artificial Intelligence, IJCAI-2021 [arXiv]
also presented virtually at 5th Workshop on Geometry and Machine Learning (WaGoML), at SoCG-21 [slides]

Teaching and Service

Teaching Assistance
- TA for Design and Analysis of Algorithms (E0 225 @ IISc), Fall 2021 (Instructors: Rahul Saladi & Siddharth Barman)
- TA for Game Theory & Mechanism Design (E1 254 @ IISc), Spring 2022. (Instructor: Y. Narahari)
- Recitation Section Leader for Basic Algorithms (CSCI-UA.0310 @ NYU), Fall 2025. (Instructor: Oded Regev)
Voluntary Peer Reviewer for ML conferences
- AISTATS (2022 Top Reviewer - 10% ; 2024)
- NeurIPS (2023 Top Reviewer )

Industry Experience

Software Development Engineer with Microsoft, Hyderabad (2015-19) : Team STCI (Search Technology Center - India)
- - Bing Local Content - Created faster pipelines for time-critical offers data. Developed and automated an E-E workflow for Healthcare experience for GB market with NHS data. Owned the Review Pipeline, developed multiple features, served as a POC for the entire Review experience. Shipped a richer answer (mobile and desktop) for Chain queries with curated data.
  - Bing Local UX - Built user experiences in bing.com for the following: LinkedIn professionals experience; Pulse feedback module (experimental); a major revamped Task-pane answer for GB market; a Refreshed Hours of Operations module.

Visiting Researcher with Meta, New York City (2023-25) : Team FAIR (Fundamental AI Research)
- - Worked with Max Nickel and Arpit Agarwal on research problems in the space of multi-agent learning in the presence of strategic agents, motivated by real world recommender systems.

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