Developing and applying models for realistic representation of travel behavior 

Advancing discrete choice models (using machine/deep learning techniques)

Developing methodologies for accurate travel demand forecasting and analysis 

Exploring how psychological factors influence human decision-making 

Applying data analytics to understand mobility patterns in large-scale cities

Examining the impacts of emerging mobility options and behavioral changes 

Analyzing public transit networks and routes

Studying interactions between transportation systems and urban space (land use) 

Assessing the effects of transport policies

Conducting simulations and feasibility assessments for transportation infrastructure planning

Combining active and passive data

Developing methodologies that integrate theory-driven and data-driven approaches