About me

I am a Ph.D. candidate in Electrical and Computer Engineering at Vanderbilt University, specializing in sequential decision-making under uncertainty and sparse rewards. My research sits at the critical intersection of transportation and energy systems — where I design algorithms that make optimal decisions now while facing deep uncertainty about the future.

To solve this, I combine Mixed Integer Linear Programming (MILP), Model Predictive Control (MPC), and Reinforcement Learning (RL) to deploy robust coordination policies for cyber-physical systems. A distinctive aspect of my work is embedding negotiation mechanisms within sequential decision-making frameworks, reconciling the individual goals of EV drivers with the collective needs of the energy grid.

Highlights

• 14 publications across top venues including AAMAS (2025, 2026), ACM/IEEE ICCPS (2025, 2026), IEEE ITSC, ACM e-Energy, and IEEE BigData
• Best Paper Award Finalist — AAMAS 2025 (Top 5% of submissions)
• Best PhD Forum Poster Award — ACM/IEEE ICCPS 2025
• 2nd Place, Best Poster — INFORMS 2025 Annual Meeting
• Russell G. Hamilton Scholar — Vanderbilt University
• OpenMinds NextGen Leader 2025 — Energy & Climate leadership cohort
• Industry Collaboration — Research Intern at Nissan North America (V2B optimization, 50k+ telematics records analyzed)
• Open-Source Impact — Co-developed E-Transit-Bench, MoveOD, and OPTIMUS simulation tools used by academic and industry partners

Beyond Research

I’m passionate about building things — both in software and in the physical world. Outside the lab, I design and build RC planes and drones, work with 3D printing for rapid prototyping, and have a background in VLSI design from my undergraduate studies in Electronics and Communication Engineering. I enjoy reading comics and stay engaged with the maker community. These hands-on interests inform my systems thinking and complement my research in cyber-physical systems.