Eeshan Bhaduri

Background

About Eeshan Bhaduri

Eeshan is a postdoctoral Research Fellow at the Institute for Transport Studies (ITS), University of Leeds, working with Prof. Charisma F Choudhury on the UKRI-funded NEXUS project. His research focuses on developing next-generation activity-travel behaviour models by integrating data science with traditional transport modelling. He specialises in working with large-scale passive data sources, leveraging data-driven methods (ML, DL, and AI) to understand and predict travel decisions in rapidly evolving urban landscapes. Previously, he contributed to the UKERC project alongside Prof. Zia Wadud and Jillian Anable, examining how Connected Autonomous Vehicles (CAVs) could influence the UK’s net-zero goals. Eeshan holds a PhD in Transportation Planning from the Indian Institute of Technology (IIT) Kharagpur, where he developed a framework for the sustainable operation of ride-hailing services. He also completed an MTech in Infrastructure Design and Management from IIT Kharagpur, following a BArch from IIEST Shibpur. During his postgraduate studies, he was a DAAD scholar and exchange student at the Technical University of Munich (TUM), working under Prof. Rolf Moeckel. With multidisciplinary expertise spanning transport, data science, energy, and urban infrastructure, Eeshan has contributed to major national consultancy projects in India and collaborated internationally with researchers across continents. He has published over 10 peer-reviewed articles and is an active member of several professional bodies, including WCTRS-Y, TRB’s Young Members Subcommittee, and TRG India. He currently serves as the Early Career Researcher (ECR) representative at ITS and is affiliated with the Priestley Centre for Climate Futures. If you're interested in learning more about his work or exploring collaboration opportunities, feel free to DM on LinkedIn, email at (E.Bhaduri@leeds.ac.uk) and check out his website (https://sites.google.com/view/eeshanbhaduri/home). Areas of expertise: Travel behaviour modelling; Data Science; Emerging mobility systems; Emission and Energy impact modelling; Transportation in developing countries; Sustainable transportation; Evidence-based policy evaluation