Archie Huang, Ph.D.

Dr. Archie Huang joined the BCEE department at Concordia University in 2025. Previously, he served as a research assistant professor at Tennessee Tech University, and worked as a postdoctoral research associate at the University of Connecticut. His research and work interests include traffic state estimation, nonlocal traffic flow dynamics, traffic modeling with variable speed limits, and physics-informed deep learning.

Education

Ph.D., Civil Engineering, University of Central Florida, 2023
M.S., Applied Urban Science and Informatics, New York University, 2016
B.Eng., Electrical Engineering, Tsinghua University, 2012 

Courses

CIVI 372 Transportation Engineering (Fall 2025)

Journal Publications

• Kachroo, P., Agarwal, S., & Huang, A. J. (2025). An Architecture for Signal Free Intersection Involving Autonomous Vehicles. In Models and Methods for Systems Engineering (pp. 97-107). Cham: Springer Nature Switzerland.
• Huang, A. J., Biswas, A., & Agarwal, S. (2024). Incorporating nonlocal traffic flow model in physics-informed neural networks. IEEE Transactions on Intelligent Transportation Systems.
• Kachroo, P., Agarwal, S., Biswas, A., & Huang, A. J. (2023). Nonlocal calculus-based macroscopic traffic model: Development, analysis, and validation. IEEE Open Journal of Intelligent Transportation Systems, 4, 900-908.
• Huang, A. J., & Agarwal, S. (2023). On the limitations of physics-informed deep learning: Illustrations using first-order hyperbolic conservation law-based traffic flow models. IEEE Open Journal of Intelligent Transportation Systems, 4, 279-293.
• Huang, A. J., & Agarwal, S. (2022). Physics-informed deep learning for traffic state estimation: Illustrations with LWR and CTM models. IEEE Open Journal of Intelligent Transportation Systems, 3, 503-518.
• Muhlmeyer, M., Agarwal, S., & Huang, A. J. (2020). Modeling social contagion and information diffusion in complex socio-technical systems. IEEE Systems Journal, 14(4), 5187-5198.
• Kachroo, P., Saiewitz, A., Raschke, R., Agarwal, S., & Huang, A. J. (2020). A New Language and Input–Output Hidden Markov Model for Automated Audit Inquiry. IEEE Intelligent Systems, 35(6), 39-49.
• Muhlmeyer, M., Huang, A. J., & Agarwal, S. (2019). Event triggered social media chatter: A new modeling framework. IEEE Transactions on Computational Social Systems, 6(2), 197-207.

Book Chapter

Kachroo, P., Agarwal, S., & Huang, A. J. (2025). An Architecture for Signal Free Intersection Involving Autonomous Vehicles. In Models and Methods for Systems Engineering (pp. 97-107). Cham: Springer Nature Switzerland.

Conference Proceedings

• Huang, A. J., & Filipovska, M. (2024, September). Physics-Informed Bayesian Deep Learning for Traffic State Estimation and Uncertainty Quantification. In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) (pp. 4288-4293). IEEE.
• Saiewitz, A., Raschke, R., Kachroo, P., Agarwal, S., & Huang, A. J. (2021). Can artificial intelligence detect biased client statements to improve the auditor-client inquiry process?. Accounting Research Conference
• Huang, A. J., & Agarwal, S. (2020, September). Physics informed deep learning for traffic state estimation. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) (pp. 1-6). IEEE.

Referee Activities

• IEEE Transactions on Intelligent Transportation Systems (T-ITS).
• IEEE International Intelligent Transportation Systems Conference (ITSC).
• Transportation Research Board (TRB) Annual Meeting.
• IEEE Internet of Things Journal (IoT-J).
• IEEE Transactions on Systems, Man, and Cybernetics (SMC).
• IEEE Conference on Decision and Control (CDC).
• International Federation of Automatic Control (IFAC) Symposium on Control in Transportation Systems.