Vishal is doing his Ph.D. and co-leading the TraMPA project at the chair of Transportation Systems Engineering, Technical University of Munich (TUM). Vishal holds a bachelor’s degree in Civil engineering from the Indian Institute of Technology Roorkee, India, and a master of science in Transportation Systems from the Technical University of Munich, Germany. He has worked as a Deputy Manager (Tech.) at the National Highways Authority of India for more than four years and as a Student Research Assistant in machine learning at Fortiss GmbH.
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 my 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.: One-shot heuristic and ensembling for automated calibration of large-scale traffic simulations. preprint, 2023
- Mahajan, V., Barmpounakis, E., Alam, Md R., Geroliminis, N., Antoniou, C.: Treating Noise and Anomalies in Vehicle Trajectories from an Experiment with a Swarm of Drones. in review, 2022
- Mahajan, V., Cantelmo, G., Rothfeld, R., Antoniou, C.: Predicting network flows from speeds using open data and transfer learning. IET Intell. Transp. Syst. 00, 1– 21 (2022).
- 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. Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich. Eur. Transp. Res. Rev. 13, 26 (2021).
- 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.