Rahul Sengupta

Orcid: 0000-0001-9793-5176

According to our database1, Rahul Sengupta authored at least 13 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
MTDT: A Multi-Task Deep Learning Digital Twin.
CoRR, 2024

Graph Attention Network for Lane-Wise and Topology-Invariant Intersection Traffic Simulation.
CoRR, 2024

A Data-driven Approach for Probabilistic Traffic Prediction and Simulation at Signalized Intersections.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

2023
Computing Arterial Travel Time Distributions From Loop Detector and Probe Datasets.
IEEE Trans. Intell. Transp. Syst., November, 2023

Using DSRC Road-Side Unit Data to Derive Braking Behavior.
Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems, 2023

Towards Effective Traffic Signal Safety and Optimization Using Fisheye Video.
Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems, 2023

2022
Subcycle Waveform Modeling of Traffic Intersections Using Recurrent Attention Networks.
IEEE Trans. Intell. Transp. Syst., 2022

A Modern Intersection Data Analytics System for Pedestrian and Vehicular Safety.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

2021
Subcycle-based Neural Network Algorithms for Turning Movement Count Prediction.
Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, 2021

TQAM: Temporal Attention for Cycle-wise Queue Length Estimation using High-Resolution Loop Detector Data.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

2020
A Platoon Matching Approach for the Estimation of Arterial Travel Time Distributions.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2017
DeepPositioning: Intelligent Fusion of Pervasive Magnetic Field and WiFi Fingerprinting for Smartphone Indoor Localization via Deep Learning.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

2016
Identifying Nontechnical Power Loss via Spatial and Temporal Deep Learning.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016


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