Conducted applied research sponsored by DOE/VTO in real-time lane-level vehicle localization forvehicle platooning vehicular network using a hybrid sensor fusion scheme based on EKF, map-matching, and vision-based lane detection using commercial sensor setup, a subtask for the connected driving aplication project.

• Undergraduate research apprentice participating in the EECS MEng team for the BISTRO capstone project, an open-source Collaborative Planning Support System designed to conduct optimization on congestion pricing experiments in urban city scenarios.

• Conducted network mode choice and travel time calibration and optimization on the agent-based, link-level BEAM simulations based on Sioux Falls, SD and San Francisco, CA study scenarios.

• Created geo-spatial visualizations to interpret the simulation outputs from cordon/per-mile road pricing policies aimed to reduce traffic congestion and cost burden.

• Managed AWS database parsing pipelines for visual dashboard.