Research
My group studies learning and control methods for systems in which people, physical infrastructure, and data interact. Our work connects mathematical models with data-driven evaluation and real-world implementation.
Electric Mobility and Energy Coordination
We design control and optimization methods for electric taxi fleets, shared micromobility, charging infrastructure, demand response, renewable energy, and short-term power disruptions. The goal is to reduce energy cost and support the power system while maintaining transportation service quality.
Urban Computing and Municipal Services
We study municipal service demand, service-time estimation, resource scheduling, and conflicts among city services. Our methods combine spatial-temporal learning, causal analysis, optimization, and multi-agent coordination to support more reliable urban services.
Smart Infrastructure and the Internet of Things
We use connected sensing, edge computing, and data-driven control to improve buildings and infrastructure. Topics include indoor environmental quality, occupancy modeling, heating and cooling control, federated intelligence, and edge-assisted autonomous systems.