Associate Professor

Qi Han


Dr. Qi Han is an associate professor of sustainability transition in the built environment. Her research interests include modelling the transition process in the urban environment, behaviour change and data-driven technology in resource optimization. She has been working on various topics linked with resource optimization in terms of land use, building material, social network analysis, CO2, and energy transition. In contribution to big data and AI, she has developed various simulation models to efficiently provide decision support for planners and policymakers. Her recent works include also natural-based solutions for resilient cities, the application of AI algorithms in resource optimization regarding energy efficiency and CO2 reduction, and circular buildings. She supervises PhDs and master students, works on EU funded projects in smart cities, and energy transition, and is involved in the teaching of process modelling courses. She is a guest editor of journals and serves constantly as an ad hoc reviewer for many journals and conferences in planning, energy, environment management, and sustainable city and society.

It is people’s creativity in finding new ways of interacting with one another, with the built environment that makes the world interesting and challenging.”


Qi Han obtained her PhD in Urban Planning from TU/e, with a thesis named ‘Modeling Strategic Behavior in Anticipation of Congestion’. She also holds an MSc in Urban Planning and Development from Tohuku University, Japan, and a BSc in architect from Tongji University, China. 

Qi has been published in Journal of Cleaner Production, Journal of Environment Management, Sustainable Cities and Society, Energy Policy, Cities, International Journal of Project Management, Ecological Indicator, Land Use Policy, Applied Geography, Environment and Planning B, Journal of Urban Planning and Development, etc. She serves as a reviewer for international journals and conferences and acts as co-promotor in PhD projects. She is also involved in the TU/e Data Science Center Eindhoven (DSC/e) Big Data Alliance and a formal member of the Eindhoven Institute for Renewable Energy Systems: EIRES.