Biography
Dr. Agnimitra Sengupta joined the Civil Engineering faculty as an Assistant Professor in the School of Science, Engineering, and Technology at Penn State Harrisburg in 2025. He holds a Ph.D. and M.S. in Civil Engineering from Penn State University, with a focus on transportation systems. Prior to joining Penn State Harrisburg, Dr. Sengupta worked in the transportation industry, where he specialized in traffic operations and safety. Dr. Sengupta’s research interests include traffic safety and operations, infrastructure management and the application of artificial intelligence and machine learning in transportation systems. He currently serves as a member of the Standing Committee on Testing and Evaluation of Transportation Structures of the Transportation Research Board and as a panel member for a National Cooperative Highway Research Program project.
Research Interests
- Transportation systems; traffic safety and operations
- Infrastructure management; statistical and econometric modeling; machine learning
- Artificial intelligence
Publications
Sengupta A. and Guler S.I. (2023). Deep Learning-based spatial translation of traffic prediction using Newell’s theory. ASCE Journal of Transportation Engineering, Part A: Systems. 151 (7).
Hoxha E.*, Feng J., Sengupta A., Kirakosian D., He Y., Shang B., Gjinofci A. and Xiao J. (2024) Contrastive learning for robust defect mapping in concrete slabs using impact echo. Construction and Building Materials, 461, DOI: 10.1016/j.conbuildmat.2024.139829
Papakonstantinou K., Guler S.I., Gayah V., Bhattacharya A., Saifullah M., Sengupta A. and Lu M. (2024). Quantifying the impact of data unavailability, inaccuracies, and uncertainty on deterioration modeling and infrastructure asset management. CIAMTIS US DOT Region 3 University Transportation Center, Final Report CIAM-UTC-REG41
Sengupta A., Mondal S., Das A.* and Guler S.I. (2024). A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models. Transportation Research Part C: Emerging Technologies, 162, DOI: 10.1016/j.trc.2024.104585
Sengupta A., Guler S.I., Gayah V. and Warchol S. (2024). Evaluating the reliability of automatically generated pedestrian and bicycle crash surrogates. Accident Analysis and Prevention, 203, DOI: 10.1016/j.aap.2024.107614
Savolainen P., Gates T., Johari M., Bamney A., Jashami H., Gupta N., Abatan A., Donnell E., Guler S.I., Sengupta A., Smaglik E., Gooch J. and Hallmark S. (2024). NCHRP Report 1081: Acceleration, deceleration, and stopping sight distance criteria for geometric design of highways and streets. NCHRP Research Project 15-75, DOI: 10.17226/27490
Prajapati A.*, Sengupta A. and Guler S.I. (2023). Accounting for traffic dynamics in pavement maintenance scheduling. Transportation Research Record, DOI: 10.1177/03611981231206176
Sengupta A., Azari H., Guler S.I. and Shokouhi P. (2023). Validating a physics-based automatic classification scheme for impact echo signals on data using a concrete slab with known defects. Transportation Research Record, DOI:10.1177/03611981231173649
Mahmud A., Sengupta A. and Gayah V. (2023). Crash classification by manner of collision: A comparative study. Transportation Letters: The International Journal of Transportation Research. DOI:10.1080/19427867.2023.2175419
Sengupta A., Mondal S., Guler S.I. and Shokouhi P. (2022). A hybrid hidden Markov model and time-frequency approach to Impact Echo signal classification. Journal of Nondestructive Evaluation. 41(69). DOI:10.1007/s10921-022-00901-1
Sengupta A., Gayah V. and Donnell E.T. (2021). Examining the impacts of crash data aggregation on SPF estimation. Accident Analysis and Prevention. 160. DOI: 10.1016/j.aap.2021.106313
Sengupta A., Guler S.I. and Shokouhi P. (2021). Interpreting impact echo data to predict condition rating of concrete bridge decks: A machine-learning approach. ASCE Journal of Bridge Engineering. 26(8). DOI: 10.1061/(ASCE)BE.1943-5592.0001744
Education
Ph. D, Civil Engineering, Pennsylvania State University
M.S., Civil Engineering, Pennsylvania State University
B.E., Construction Engineering, Jadavpur University