Kailai Wang Research Lab

Yuhao Wang’s research focuses on GeoAI, spatial network science, and transportation cybersecurity. He uses spatiotemporal modeling, spatial reasoning, and remote sensing-based computer vision to examine human-environment interactions across urban dynamics, human mobility, cybercrime, street networks, and extreme weather. Current work explores Geographic Manifold Hypergraph Convolutional Network (Geo-MHGCN), Spatial Transformer Network (STN), and GeoAI agents, with applications to cybercrime prediction, transportation resilience, and industry clustering of transportation cybersecurity.

Yixuan Huang’s research focuses on transportation and energy systems, particularly hydrogen transportation and energy infrastructure. She applies optimization, machine learning, and data driven methods to analyze planning and decision-making problems. Her current work includes hydrogen transportation networks, hydrogen vehicle adoption, and AI assisted planning and permitting for energy infrastructure.

Chuyue Wang’s research focuses on AI-driven optimization for electric vehicle battery recycling and circular supply chains. She combines machine learning, statistical modeling, spatial analysis, and optimization to study battery retirement flows, recycling capacity, reverse logistics, and facility siting. Her current work explores how data-driven and AI-enabled methods can support more efficient, resilient, and sustainable battery recycling infrastructure and supply chain decisions.

Jinghang Gao’s research focuses on transportation cybersecurity resilience, travel behavior, and human-centered infrastructure systems. He integrates spatial analytics, econometric, machine learning, and optimization methods to examine how disruptions, emerging technologies, and the built environment affect mobility. His current work addresses public transit cybersecurity and recovery, campus travel behavior and transportation access, and extreme-weather impacts on urban systems, supporting more resilient, equitable, and adaptive transportation.