About
I am a fourth-year Ph.D. student in Computer Science at the University of Georgia working in the Modeling, Simulation & Analytics Lab (MSAL) under the supervision of Dr. John A. Miller.
I am building empirically validated discrete-event microscopic traffic simulation models of real transportation systems, and I am developing an agentic architecture where LLM-driven agents autonomously design, execute, and refine simulation experiments for scientific knowledge discovery.
I am actively extending the ScalaTion 2.0 simulation framework with lane-level validation, constrained calibration infrastructure, and structural intervention modeling for high-stakes infrastructure scenarios, using empirical sensor data from the California Performance Measurement System (PeMS) to support counterfactual infrastructure policy evaluation.
Dissertation Theme
I am investigating the following central dissertation question:
Can we build empirically validated discrete-event microscopic traffic simulation models that are trustworthy enough for counterfactual infrastructure policy evaluation under extreme disruption, and can agentic simulation systems autonomously design, execute, and refine such experiments at scale?
This proposal targets scientific knowledge discovery through validated, agent-guided discrete-event microscopic traffic simulation experiments that reveal mechanisms, thresholds, and policy-relevant trade-offs under extreme disruption.
This research integrates:
- Discrete-event and time-stepped microscopic traffic simulation
- Simulation-based optimization
- Lane-level empirical validation of microscopic traffic models
- Agent-guided design and execution of simulation experiments
- Infrastructure resilience modeling
I am working to build data-calibrated discrete-event microscopic traffic simulation models of urban freeway corridors, enabling scalable agent-guided experiment generation and evaluation for high-stakes infrastructure scenarios.