PhD student in Industrial & Systems Engineering at The Ohio State University, working at the Center for Automotive Research (CAR). My research focuses on graph neural network-based intrusion detection for in-vehicle networks, with an emphasis on knowledge distillation for deploying lightweight models on resource-constrained automotive platforms.
Research Interests
- Graph neural networks for cybersecurity in automotive systems
- Knowledge distillation and model compression for edge deployment
- Federated learning for privacy-preserving intrusion detection
- LLM behavior in game-theoretic scenarios
Recent Projects
Ohio Campaign Finance Dashboard — Interactive data visualization platform exploring political contributions across Ohio legislative districts. Built with D3.js, DuckDB-WASM, and Observable Framework.
Mobility Systems Lab Documentation — Technical knowledge base for lab onboarding, covering HPC workflows, PyTorch/PyG setup, and SLURM job management.
CAIS 2025 Capstone — Empirical investigation of LLM behavior in game-theoretic scenarios (prisoner’s dilemma, battle-of-the-sexes, duopoly markets).
Technical Skills
ML/DL: PyTorch, PyTorch Geometric, Ray, scikit-learn, Weights & Biases
Data: DuckDB, Spark, Hadoop, SQL, Pandas
Infrastructure: AWS, Azure, SLURM, Git, Linux