Welcome!
In the Smart Mobility Lab, we explore the many layers that shape how people and goods move through cities. Our research focuses on how technology, infrastructure, and human behavior interact to create mobility systems that are efficient, resilient, and sustainable.
We combine advanced modeling, optimization, simulation, and data-driven analysis to better understand, predict, and design future transportation systems. Below are some of our ongoing research directions:
- Generating and fusing multimodal datasets to overcome data scarcity and improve the robustness of modeling and decision-making in transportation systems.
- Understanding travel patterns and dynamics in existing mobility systems using data analytics and mathematical models.
- Modeling mobility as an interconnected system, capturing its links to energy, environment, and other urban networks.
- Designing and optimizing operations and mobility services that improve network performance and adaptability.
- Investigating long-term impacts of transportation infrastructure on communities and their resilience.
Areas of Expertise
- Transportation Network Modeling
- Operations and Policy Optimization
- Reinforcement Learning and System Dynamics
- Resilience and Sustainability in Mobility Systems
- Agent-based and Network Simulation
- Dataset Generation and Fusion for Data-Scarce Environments
Prospective Students
Our team is seeking driven and curious graduate students to join us starting Fall 2026. This is an exciting opportunity to be part of a group that tackles big, real-world transportation challenges with creativity, rigor, and purpose.
We work at the intersection of data, modeling, and systems thinking to understand and improve how mobility networks operate and evolve. If you’re excited by complex problems, eager to build new tools and frameworks, and want your work to have a lasting impact on the way people move and cities function, we want to hear from you.
Interested students should send a CV, transcripts, and any relevant papers (if available) to be considered for graduate research opportunities.