PhD Researcher · Georgia Tech

Hi, I'm Bhavini
Jeloka

PhD in Machine Learning at GeorgiaTech
Advised by Prof. Panagiotis Tsiotras

I study how intelligent agents learn to make decisions in complex, competitive environments. My research bridges reinforcement learning, game theory, and decision making — with a focus on multi-agent systems at scale.

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Research Focus

What I Work On

🎮

Multi-Agent Game Theory

Studying strategic interactions between large numbers of rational agents using mean-field game frameworks and equilibrium concepts.

🧠

Reinforcement Learning

Developing algorithms for agents to learn optimal policies in complex, high-dimensional, partially observable environments.

🎯

Control Theory

Bridging data-driven methods with classical control systems, including differential flatness and Gaussian process approaches.

Updates

News & Milestones

Recent happenings from my research journey.

Sep 2026

🏆 Paper accepted at the DynaFront Workshop, NeurIPS 2026 on risk-averse multi-population mean-field games.

Sep 2026

🏆 Paper accepted at NeurIPS 2026 (Main Conference Track): "Learning Large-Scale Competitive Team Behaviors with Mean-Field Interactions."

Jul 2026

🏆 Paper accepted at CDC 2026: "Robust Mean-Field Games with Risk Aversion and Bounded Rationality."

May 2025

🎤 Presented at the ALA (Adaptive and Learning Agents) Workshop, AAMAS 2025 on competitive team behavior learning with mean-field games.

Jul 2024

📑 Paper published at American Control Conference (ACC) 2024: "Data-Driven Control of Adaptive Cruise Control Systems using Differential Flatness and Gaussian Processes."

Aug 2023

🎓 Started PhD in Machine Learning at Georgia Institute of Technology under the supervision of Prof. Panagiotis Tsiotras.

Research

Selected Publications

Highlights from recent work. View all publications →

Workshop 2026

Risk-Averse Multi-Population Mean-Field Games

Bhavini Jeloka, Siddhartha Ganguly, Panagiotis Tsiotras

We introduce a new paradigm: risk-averse multi-population mean-field games, where each population optimizes a worst-case expected reward over dynamically feasible ambiguity sets of mean-field flows of a subset of the other populations.

PDF

Conference 2026

Robust Mean-Field Games with Risk Aversion and Bounded Rationality

Bhavini Jeloka, Yue Guan, Panagiotis Tsiotras

We study mean-field games under bounded rationality and risk-averse objectives, developing robust equilibria that account for uncertainty in initial distributions of the population.

arXiv

Conference Workshop 2025

Learning Large-Scale Competitive Team Behaviors with Mean-Field Interactions

Bhavini Jeloka, Yue Guan, Panagiotis Tsiotras

We propose a scalable reinforcement learning approach for competitive team-games using mean-field approximations coupled with online opponent model estimation.

PDF

Conference 2024

Data-Driven Control of Adaptive Cruise Control Systems Using Differential Flatness and Gaussian Processes

Bhavini Jeloka, Florentina Nicolau, Adnane Saoud, Ravi N. Banavar

A data-driven control framework for ACC systems leveraging differential flatness to simplify trajectory planning and GPs for uncertainty quantification.

PDF

See All Publications →

Background

About Me

I am a Machine Learning PhD student at the Georgia Institute of Technology, Atlanta. I work in the Dynamics and Control Systems Laboratory (DCSL) under the guidance of Prof. Panagiotis Tsiotras. My research sits at the intersection of game theory, reinforcement learning, and decision making. I am particularly interested in how large populations of strategic agents can learn to cooperate or compete — and how we can design systems that are safe, risk-averse and robust to uncertainties.

Before Georgia Tech, I earned my undergraduate and master's degrees at IIT Bombay where I worked on control theory and analysis, particularly, learning-based control and geometric mechanics.

When I am not working on mathemtical proofs or training neural networks (hyperparameter tuning yay!), you can find me running around Atlanta, lifting weights, scouting for coffee shops or cooking.