Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

Professor of Transport Risk and Safety



+44 (0)20 7594 6037a.majumdar




Mrs Maya Mistry +44 (0)20 7594 6100




604Skempton BuildingSouth Kensington Campus





Dr Arnab Majumdar is the Professor of Transport Risk and Safety and the Director of the Lloyds Register Foundation Transport Risk Management Centre (LRF TRMC) at the Centre for Transport Studies, Imperial College London. He is also the Deputy Director(External Partnerships) of the ESRC London Interdisciplinary Social Science Doctoral Training Partnership (LISS DTP), involving the Universities of Kings College London, Queen Mary and Westfield and Imperial College London.He is also a Chartered Engineer and a Fellow of the Chartered Institute of Highways and Transportation. In addition he is a Foreign Expert at the State Key Laboratory in Air Traffic Management at the Nanjing University of Aeronautics and Astronautics, China.

His PhD was completed in 2003 at Imperial College on the Estimation of Airspace Capacity in Europe. He also has MSc. degrees in Transport from Imperial College and Cognitive Neuropsychology from University College London.

He has over 25 years research and teaching experience in risk and safety in transport, in particular air transport. His specialty is in the investigation of problems in Air Traffic Management (ATM) and Air Traffic Control (ATC) internationally. Of particular interest are human performance related aspects of operators, in particular workload and complexity issues faced by Air Traffic Controller (ATCo) and fatigue. In recent years his research has focused on the human and social factors associated with human behaviour when there is a threat to life, e.g. during a knife attack, fire and toxic substances. To do this he has used a combination of experimental methods including virtual reality and wearable technologies.

Dr Majumdar has published over 100 peer-reviewed Journal papers, over 120 Conference papers and three book chapters. He is a Member of three international aviation research committees and received numerous awards, including a Best Paper award in Airspace Management at the 6th USA/Europe ATM 2005 R&D Seminar and the Written Paper Prize Silver Award for the best papers published in The Aeronautical Journal in 2019. 

In conducting his research, he has worked closely with a number of organisations both nationally, e.g. Public Health England, Abellio, easyJet, and internationally, e.g. Transport Canada, SINTEF (Norway) SESAR JU, Dutch State Railways.

 Dr Majumdar has successfully supervised 20 PhD students. He currently leads an eight-person team of doctoral students and research associates at the LRF funded TRMC covering a broad spectrum of research assessing human and social factors in risk safety of safety critical systems, including human behaviour during evacuation from emergencies.  He has won over £2.5 million in research funding from the Lloyds Register Foundation, the UKRI and the European Union.

In addition to research and doctoral supervision, Dr. Majumdar lectures on the following modules:

  • transport safety and risk at the MEng and MSc. level;
  • highway engineering at the MEng and MSc. level;
  • air traffic management at the MSc. Level.
  • The Science of Crowds: Movement, Behaviour and Design at the Year 2 and Year 3 I-Explore level.



Magnusdottir EH, Johannsdottir KR, Majumdar A, et al., 2022, Assessing Cognitive Workload Using Cardiovascular Measures and Voice, Sensors, Vol:22, Pages:6894-6894

Long F, Carter H, Majumdar A, 2022, Casualty behaviours during incidents involving hazardous materials, Safety Science, Vol:152, ISSN:0925-7535, Pages:105758-105758

Rahman AU, Saeed M, Mohammed MA, et al., 2022, Supplier selection through multicriteria decision-making algorithmic approach based on rough approximation of fuzzy hypersoft sets for construction project, Buildings, Vol:12, ISSN:2075-5309, Pages:1-20

Abbas T, Ali SF, Mohammed MA, et al., 2022, Deep learning approach based on residual neural network and SVM classifier for driver’s distraction detection, Applied Sciences, Vol:12, ISSN:2076-3417, Pages:6626-6626

Abbas Y, Martinetti A, Houghton R, et al., 2022, Disentangling large scale technological projects: learning from ERTMS roll-out case study in the Netherlands, Research in Transportation Business & Management, ISSN:2210-5395, Pages:100856-100856

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