Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

Chair in Intelligent Transport Systems



+44 (0)20 7594 6121m.quddus Website




Ms Maya Mistry +44 (0)20 7594 6100




308Skempton BuildingSouth Kensington Campus





Mohammed Quddus is Chair in Intelligent Transport Systems in the Department of Civil and Environmental Engineering at Imperial College London.  Professor Quddus received his PhD in Intelligent Transport Systems from Imperial College London in 2006. He obtained his master’s degree in Transport Engineering from the National University of Singapore in 2001 and his bachelor’s degree in Civil Engineering from the Bangladesh University of Engineering and Technology (BUET) in 1998, Bangladesh. Prior to joining Imperial, he was the Professor of Intelligent Transport Systems and Head of Transport and Urban Planning Group at the School of Architecture, Building and Civil Engineering at Loughborough University.

Professor Quddus is renowned internationally for his ground-breaking research in transport safety, autonomous and connected mobility, big data analytics and map-matching for Intelligent Transport Systems (ITS). His seminal papers on AI-based map-matching algorithms have been influential and highly cited by researchers world-wide and implemented by the ITS industry, car manufacturers and National Highways (UK).

The vision of future transport is increasingly based on the concept of Intelligent Mobility (IM) where the connected capabilities of partially and fully autonomous vehicles, road infrastructure and traffic management systems place people and goods at the heart of the transport system. New intelligent technologies could deliver a step change in safety and mobility but they bring many research challenges. With this in mind, Prof Quddus has been working with his Research Associates, PhD students and colleagues from other disciplines, universities and industry in the areas of operations, planning and risk assessment of autonomous or semi-autonomous vehicles. 

His research projects have been primarily funded by the UK Engineering and Physical Sciences Research Council (EPSRC), National Highways, Department for Transport (UK) and the European Union (EU). He has an excellent track record in mentoring and supervising post-doctoral researchers and PhD students. So far, he has authored/co-authored over 110 journal articles, 120 conference papers, six book chapters and 20 technical reports that have accumulated a total of 11,500 citations from researchers all around the world. He serves as an Associate Editor of a prestigious Journal - Transportation Research Part C: Emerging Technologies and a member of TRB (Transportation Research Board, USA) committee on Safety Data, Analysis and Modelling.

Google Scholar Profile:
‪Mohammed Quddus‬ - ‪Google Scholar‬

Research Gate Profile:
Mohammed Quddus | Scores (

LinkedIn Profile:
Mohammed Quddus | LinkedIn



Yi D, Fang H, Hua Y, et al., 2022, Improving Synthetic to Realistic Semantic Segmentation With Parallel Generative Ensembles for Autonomous Urban Driving, Ieee Transactions on Cognitive and Developmental Systems, Vol:14, ISSN:2379-8920, Pages:1496-1506

Man CK, Quddus M, Theofilatos A, et al., 2022, Wasserstein generative adversarial network to address the imbalanced data problem in real-time crash risk prediction, Ieee Transactions on Intelligent Transportation Systems, Vol:23, ISSN:1524-9050, Pages:23002-23013

Formosa N, Quddus M, Ison S, et al., 2022, A new modelling approach for predicting vehicle-based safety threats, Ieee Transactions on Intelligent Transportation Systems, Vol:23, ISSN:1524-9050, Pages:18175-18185

Alotaibi S, Quddus M, Morton C, et al., 2022, Transport investment, railway accessibility and their dynamic impacts on regional economic growth, Research in Transportation Business and Management, Vol:43, ISSN:2210-5395

Enoch M, Monsuur F, Palaiologou G, et al., 2022, When COVID-19 came to town: Measuring the impact of the coronavirus pandemic on footfall on six high streets in England, Environment and Planning B: Urban Analytics and City Science, Vol:49, ISSN:2399-8083, Pages:1091-1111

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