I am an Assistant Professor in the Department of Civil and Architectural Engineering and Construction Management at the University of Wyoming. My research lies at the intersection of transportation science, multimodal and generative AI, and statistical learning. I study how transportation systems can be understood, predicted, and represented from heterogeneous observations, and how physical constraints and transportation knowledge can improve the reliability and generalizability of AI models.

My work develops methods for spatiotemporal safety modeling, multimodal representation learning and reasoning, and the integration of observations and models in transportation digital twins. Key questions include how to infer traffic states and risks from incomplete data, learn representations that transfer across scenes and sensing conditions, and evaluate whether AI reasoning is grounded in observable evidence. Through model development, benchmark construction, and empirical evaluation, I aim to advance the scientific foundations of transportation AI and translate these advances into safer, more efficient transportation systems.

News

• 📌 Research positions available! If you are interested in joining my research group, please see the position posting. These positions are available while the link remains active.

• 9/2026: Our paper, Real-time lane-level abnormal traffic detection on freeways using sparse telematics data, is published in Accident Analysis & Prevention.

• 8/2026: Awarded the Roger Wilmot Memorial Fund Travel Grant, administered by UW E-RIDE, to support planned participation in TRB 2027, with a focus on multimodal AI, vehicle telematics, and research partnerships for rural transportation safety. Details.

• 8/2026: The Wisconsin Highway Delay Causation Study (2025–2026), supported by WisDOT, is complete. The study examines recurring and nonrecurring highway delay and contributing factors across Wisconsin. Final report.

• 7/2026: I was selected as a 2026–2027 UW Data Science Faculty Fellow to develop vehicle-telematics methods for real-time roadway monitoring and proactive safety management on Wyoming highways, supported by the UW Data Science Center. Details.

• 6/2026: Awarded a Wyoming NASA EPSCoR Faculty Research Award to develop lightweight vision-language models for interpreting roadway weather from camera imagery, with natural-language explanations and evaluation on edge devices. Details.

• 5/2026: SCOUT-WY received support through the UW CEPS Engineering Initiative seed grant program for 2026–2027 to link vehicle observations across sparse roadside cameras and support travel-time estimation, traffic monitoring, and anomaly detection on rural Wyoming corridors. Details.

• 5/2026: New preprint: Behavior-Grounded Lane Representation Learning for Multi-Task Traffic Digital Twins, introducing GeoLaneRep for behavior-aware traffic digital twins.

• 5/2026: We will present our work, CrashSight, at the DriveX Workshop at CVPR 2026.

• 4/2026: Our proposed Wyoming Center for Artificial Intelligence in Transportation (WyCAIT) received support from the UW Science Institute for 2026–2027 to advance multimodal sensing, resilient AI, and corridor digital twins for rural transportation safety, operations, and workforce development. Details.

• 4/2026: New preprint: An Agentic Workflow for Detecting Personally Identifiable Information in Crash Narratives, presenting a locally deployable workflow for privacy-sensitive crash data processing.

• 4/2026: New preprint: V2X-QA, a dataset and benchmark for multimodal large language models in autonomous driving across ego, infrastructure, and cooperative views.