Vishal Mahajan

About Vishal Mahajan

Vishal Mahajan, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at Technische Universität München, specializes in the field of machine learning, time series forecasting, simulation calibration.

His recent articles reflect a diverse array of research interests and contributions to the field:

Analyzing the impact of fare-free public transport policies on crowding patterns at stations using crowdsensing data

Towards automated calibration of large-scale traffic simulations

Treating Noise and Anomalies in Vehicle Trajectories from an Experiment with a Swarm of Drones

Similarity-based Feature Extraction for Large-scale Sparse Traffic Forecasting

Traffic4cast at NeurIPS 2022–Predict dynamics along graph edges from sparse node data: Whole city traffic and ETA from stationary vehicle detectors

Data to the people: a review of public and proprietary data for transport models

Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich

Crash risk estimation due to lane changing: A data-driven approach using naturalistic data

Vishal Mahajan Information

University

Position

___

Citations(all)

187

Citations(since 2020)

187

Cited By

12

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

4

i10Index(since 2020)

4

Email

University Profile Page

Google Scholar

Vishal Mahajan Skills & Research Interests

machine learning

time series forecasting

simulation calibration

Top articles of Vishal Mahajan

Analyzing the impact of fare-free public transport policies on crowding patterns at stations using crowdsensing data

Transportation Research Part A: Policy and Practice

2024/1/1

Towards automated calibration of large-scale traffic simulations

preprint

2023

Treating Noise and Anomalies in Vehicle Trajectories from an Experiment with a Swarm of Drones

IEEE Transactions on Intelligent Transportation Systems

2023/5/1

Similarity-based Feature Extraction for Large-scale Sparse Traffic Forecasting

arXiv preprint arXiv:2211.07031

2022/11/13

Traffic4cast at NeurIPS 2022–Predict dynamics along graph edges from sparse node data: Whole city traffic and ETA from stationary vehicle detectors

2022/8/31

Data to the people: a review of public and proprietary data for transport models

2022/7/4

Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich

European Transport Research Review

2021/12

Crash risk estimation due to lane changing: A data-driven approach using naturalistic data

IEEE Transactions on Intelligent Transportation Systems

2020/12/29

Prediction of lane-changing maneuvers with automatic labeling and deep learning

Transportation research record

2020/7

See List of Professors in Vishal Mahajan University(Technische Universität München)