Hi! I am a first-year Ph.D. student in Civil Engineering at the University of Southern California, advised by Prof. Ruolin Li. My research lies at the intersection of multi-agent learning, game theory, and LLM-based decision making for cyber-physical systems.

I am especially excited about macro-micro agent systems: how a system-level coordinator can shape many local agents, and how local agent behaviors feed back into global dynamics. My current projects include bounded LLM mediation for cyber-physical control, defensive population learning for competitive autonomous ride-hailing, and macro-micro reinforcement learning for mixed-autonomy mobility.

Currently thinking about: macro ↔ micro agents LLM-mediated control multi-agent RL game-theoretic learning

Email: kwang255@usc.edu

News

  • Oct 2026 Heading to INFORMS Annual Meeting in San Francisco for an oral presentation.
  • Jul 2026 Next stop: INFORMS Transportation Science and Logistics Conference at MIT.
  • Apr 2026 Shared recent work at the SoCal CEE Research Symposium at USC.
  • Jan 2026 Presented at the Transportation Research Board Annual Meeting in Washington, D.C.
  • Oct 2025 Gave an oral presentation at INFORMS Annual Meeting in Atlanta.
  • Sep 2025 Presented a poster at the USC Center for Autonomy & AI Workshop.
  • Jul 2025 Gave an oral presentation at the USC STEM Bytes Seminar.
  • Apr 2025 Presented at the SoCal CEE Research Symposium at UCI.

Publications & Under Review

DAMA framework figure from the NeurIPS submission

Out of the Loop: Bounded LLM Mediation for Cyber-Physical Control

Kexin Wang, Yizhe Guan, and Ruolin Li

Under review, NeurIPS 2026

A dual-agent LLM mediation architecture that coordinates cyber-physical agents through bounded action masking and reward shaping.

DF-PSRO overview figure from the AAAI preparation manuscript

Beyond Meta-Nash: Defensive PSRO for Robust Learning under Non-Transitive Competition

Kexin Wang, Zheng Luo, Xiyang Hu, Yue Zhao, and Ruolin Li

In preparation, AAAI 2026

A defensive population-based learning framework for robust decision-making against off-equilibrium competitive strategies.

MAPLE framework figure from the manuscript

Macro-Micro Pigouvian Multi-Agent Reinforcement Learning for Mixed-Autonomy Lane Control

Kexin Wang, Gavin Huang, Zehao Wang, Jiachen Li, and Ruolin Li

Under review, IEEE Conference on Decision and Control (CDC 2026)

A macro-micro MARL framework where lane-level Pigouvian signals coordinate decentralized CAV agents.

Highway weaving ramp figure from the manuscript

When Altruism Meets Autonomy: Managing Weaving Ramp Congestion with Strategic AVs

Kexin Wang, Haohui He, and Ruolin Li

Under review, Transportation Science

A Stackelberg-Wardrop framework for strategic autonomous agents shaping equilibrium behavior.

Mixed-autonomy ride-hailing system overview figure from the manuscript

Traffic Equilibrium in Mixed-Autonomy Network with Capped Customer Waiting

Jiaxin Hou, Kexin Wang, Ruolin Li, and Jong-Shi Pang

Under review, Transportation Research Part B

A network equilibrium model for mixed AV/HV ride-hailing fleets, customer waiting, and platform decisions.

Weaving ramp decision-making figure from the ITSC paper

To Stay or to Bypass: Unraveling Mainline Vehicles' Aggregate Strategic Decision-Making in Weaving Ramps

Haohui He, Kexin Wang, and Ruolin Li

IEEE ITSC 2025

A Wardrop-equilibrium formulation of aggregate lane-choice behavior for mainline vehicles at highway weaving ramps.

Teaching & Mentoring

  • Teaching Assistant, CE-119 Statistical Data Analysis in Engineering, USC, Fall 2025.
  • Ph.D. Mentor, USC CURVE Program, mentoring undergraduate research projects across CS, EE, and CEE, 2025-2026.

Academic Services

  • Organizer, 2026 Conference on Robot Learning (CoRL) workshop.
  • Website Designer, 2026 IFAC Workshop on Cyber-Physical Human Systems (CPHS).
  • Student Volunteer, 2026 NASA Formal Methods Symposium (NFM).
  • Reviewer, BTR 2026, IEEE CDC 2025/2026, IEEE ITSC 2026, IEEE IV 2026, IEEE ICRA 2026, TRB 2025.