Vishal currently leads the Modeling and Simulation research group at the Chair of Transportation Systems Engineering within the Technical University of Munich (TUM). His academic background includes a bachelor's degree in Civil Engineering from the Indian Institute of Technology Roorkee, India, and a master's degree in Transportation Systems from the Technical University of Munich, Germany. Prior to joining TSE, he gained experience in the industry, working as a Deputy Manager (Tech.) at the National Highways Authority of India for over four years and as a Student Research Assistant in machine learning at Fortiss GmbH.
At present, Vishal holds a research associate position at TUM while pursuing his Ph.D. His research focuses on developing Data efficient methods for modeling and simulation of transport systems. His reseach focusses on network-wide and real-time traffic estimation and prediction, large-scale transport simulation calibration, automated methods for anomaly detection, crowdsensing data for opportunistic uses, and driver behavior prediction. He is excited about applying novel machine learning methods and publicly available data to solve current challenges in transport and mobility. Notably, he served as the primary researcher on the TraMPA project, where innovative data-efficient methods were applied to address data insufficiency in transport modeling and mobility analyses. The outcomes of this project were published in prestigious peer-reviewed international journals.
Outside of work, Vishal enjoys various activities during his free time, such as running, swimming, and hiking.
His research concerns public/ open data for traffic estimation, traffic forecasting, large-scale traffic simulations, and calibration of transport models. He applies statistical, machine, and deep learning methods in his research.
Few snapshots from his research below
|December 2019 - present||Research associate and co-leading the TraMPA project.|
|August 2018 - September 2019||Student Research Assistant |
|July 2013 - September 2017||Deputy Manager (Tech.) |
National Highways Authority of India
|December 2019 - Present||Ph.D. Candidate |
Technical University of Munich (TUM)
|October 2017 - October 2019|| |
Master of Science in Transportation Systems
Crash Risk Estimation from Naturalistic Driving Data
using Machine learning
|July 2009 - May 2013||Bachelor of Technology in Civil engineering |
Indian Institute of Technology Roorkee (IITR), India
- Mahajan, V., Cantelmo, G., Antoniou, C. (2023) One-shot heuristic and ensembling for automated calibration of large-scale traffic simulations. preprint
- Mahajan, V., Barmpounakis, E., Alam, Md R., Geroliminis, N., Antoniou, C. (2023) Treating Noise and Anomalies in Vehicle Trajectories from an Experiment with a Swarm of Drones. IEEE Transactions on Intelligent Transportation Systems,
- Mahajan, V., Cantelmo, G., Rothfeld, R., Antoniou, C. (2023) Predicting network flows from speeds using open data and transfer learning. IET Intell. Transp. Syst. 00, 1– 21.
- Mahajan, V., Kuehnel, N., Intzevidou, A., Cantelmo, G., Moeckel, R., & Antoniou, C. (2021) Data to the people: a review of public and proprietary data for transport models. Transport Reviews, 0(0), 1–26.
- Mahajan, V., Cantelmo, G. & Antoniou, C. (2021) Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich. Eur. Transp. Res. Rev. 13, 26.
- Mahajan, V., Katrakazas, C., & Antoniou, C. (2022) Crash Risk Estimation Due to Lane Changing: A Data-Driven Approach Using Naturalistic Data. IEEE Transactions on Intelligent Transportation Systems, 23(4), 3756–3765.
- Mahajan, V., Katrakazas, C., & Antoniou, C. (2020). Prediction of Lane-Changing Maneuvers with Automatic Labeling and Deep Learning. Transportation Research Record, 2674(7), 336–347.