Vishal Mahajan

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.

Research Focus

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

Demand and supply calibration of large-scale simulations

Traffic flow prediction using deep learning (created using: https://github.com/jdb78/pytorch-forecasting)

Vehicle trajectories from drone videography (Data source: https://open-traffic.epfl.ch/)

Work Experience

December 2019 - present	Research associate and co-leading the TraMPA project.
August 2018 - September 2019	Student Research Assistant Fortiss GmbH
July 2013 - September 2017	Deputy Manager (Tech.) National Highways Authority of India

Education

December 2019 - Present

Ph.D. Candidate
Technical University of Munich (TUM)

October 2017 - October 2019

Master of Science in Transportation Systems
Technical University of Munich (TUM)
Thesis: Real-time Driving Intention Prediction and

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

Publications

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.