Designation: Assistant Professor
Department: Civil Engineering
Email: akshaygupta[at]iitism[dot]ac[dot]in
Contact Number: 9468617387
Office Number: +91-326-223-5539
Personal Page: Click Here
About Me: Dr. Akshay Gupta completed his Postdoctoral Research at IIT Bombay and holds a Ph.D. and M.Tech in Transportation Engineering from IIT Roorkee, along with a B.Tech from MBM Engineering College, Jodhpur. His research focuses on utilizing advanced sensors, including LiDAR and camera-based systems, to analyze driving behavior and assess crash risk. His work contributes to global initiatives like Vision Zero by advancing road safety and promoting sustainable mobility through data-driven insights.
Research Interest: Human factors, Driving Behaviour, Intelligent Transportation System, Travel Behaviour, Accessibility
1. BEST PAPER AWARD
1.World Conference of Transport Research (WCTR)-15 26th to 30th May, 2019
(Best Paper Award by Cairo University For Transport in Developing Countries)
Gupta, A., Bivina, G.R. and Parida, M. “Measuring Impact of Objective and Subjective Built Environment Factors on Access Mode Choice to Metro Stations.” International Conference World Conference on Transport Research, (WCTR)- 15 held at IIT Bombay.
2. Best Paper Award 2023 by the journal ‘Multimodal Transportation’
Chauhan V., Gupta, A. and Parida, M. Do users' characteristics really influence the perceived service quality of Multimodal Transportation Hub (MMTH)? An association rules mining approach" Multimodal Transportation Journal Award 2023
3. Outstanding Poster Award at Institute Research Day 2024 (IIT Roorkee)
Gupta, A., Choudhary P., Parida, M., Enhancing High-Speed Road Safety: Insights from Advanced LiDAR-Based Driver Behaviour Analysis.
2. ROAD SAFETY HACKATHON – ADAS
Hackathon to develop India specific Advanced Driver Assistance Systems (ADAS) products to improve road safety.
Secured Second place and cash prize of worth 5 Lac Rs. (6,015 $ USD).
3. TRAVEL GRANT
1. Gupta A., Shreyansh, Priyanshu Pansari, Choudhary P, Parida M Dynamic severity-level real -time lane departure warning system with sparse 3D-Lidar sensor. (Patent published)