Associate Professor
Department of Civil and Environmental Engineering
Department of Industrial Systems Engineering and Management
National University of Singapore
The mission of the Lab for Urban Mobility Systems (LUMOS) is to advance intelligent transportation systems, formulate new design and operational strategies, devise effective solutions to transportation problems, and bridge academic communities with industry to improve the mobility, reliability, and sustainability of transportation systems.
Our lab's research activities has been profiled at IEEE Intelligent Transportation Systems Magazine.We focus on future urban mobility and transport systems, which cover the areas of shared mobility system operation and design, travel demand and congestion management, and data-driven transportation system modeling and analysis.
The research team develops multidisciplinary approaches to address research questions with theoretical contributions and real-world implications for efficient and sustainable transportation system planning and management.
LUMOS aims to disseminate new insights, knowledge, and tools to academia, industry, government, and research organizations worldwide.
News | Dec 2025
We are thrilled to announce that our team has had two papers accepted by the ISTTT26, widely regarded as the premier venue in the field of transportation theory. The accepted works are: 1) Dynamic Senior-Centric Type Matching Optimization for Mobility-on-Demand Management in Aging Societies; and 2) Model-Supplementary Learning for Congestion Pricing: A Bias-Aware Natural Policy Gradient Approach. Congratulations!!
Journal | Dec 2025
This research is published in Communications in Transportation Research.
Presentation | Dec 2025
This research was presented in the session on intelligent transportation systems at ISMT 2025.
Presentation | Dec 2025
This research was presented in the session on connected and autonomous vehicles at ISMT 2025.
News | July 2025
Featured by the NUS Guangzhou Research Institute, Prof Liu Yang’s lab unveils an AI‑powered cooperative routing framework that harnesses connected‑vehicle data and mean‑field reinforcement learning to relieve congestion and boost urban traffic efficiency.
We are recruiting phd students and postdoctoral fellows. We are looking for researchers with strong interests and expertise in traffic simulation, mathematical modelling and programming, and data-driven optimization approaches. If you are interested in joining LUMOS, please contact Dr. Liu Yang directly by emailing to iseliuy@nus.edu.sg or ceelya@nus.edu.sg.
