Research Assistant Professor, August 2024 - Present
Tennessee Tech University
Postdoctoral Research Associate, August 2023 - August 2024
University of Connecticut
At UConn, I was interested in the research topic of the fleet rebalancing problem of shared mobility services - optimizing the fleet rebalancing approach with the aid of connected and autonomous vehicles (CAV) to reduce system-wide passenger wait time and mitigate traffic congestion.
Guest Lecturer
University of Connecticut
Transportation Planning (CE 4730 Undergraduate + CE 5730 Graduate), Fall 2023
Seminar in Transportation and Urban Engineering (CE 5030), Fall 2023
Graduate Teaching Assistant
University of Central Florida
Statics (EGN 3310), Fall 2021, Spring 2022
Applied Numerical Methods for Civil Engineering (CGN 3405), Spring 2020
Highway Engineering (TTE 3810), Fall 2019, Fall 2020
Transportation Engineering Systems (TTE 4274), Fall 2019
Teaching Assistant
California State University, Los Angeles
Fundamentals of Machine Learning (EE 4540), Spring 2018
Fleet rebalancing for shared mobility services
Simulation with connected and autonomous vehicles
Physics-informed deep learning and its applications in state estimation problems
traffic modeling with variable speed limits
Data mining for urban analytics
Ph.D., Civil Engineering, May 2023
University of Central Florida
Dissertation: Developing A Physics-informed Deep Learning Paradigm for Traffic State Estimation
M.S., Urban Informatics, August 2016
Center for Urban Science and Progress, New York University
Archie J. Huang, Animesh Biswas and Shaurya Agarwal, Incorporating Nonlocal Traffic Flow Model in Physics-Informed Neural Networks, IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3429029.
Archie J. Huang and Shaurya Agarwal, Physics-Informed Deep Learning for Traffic State Estimation: Illustrations With LWR and CTM Models, IEEE Open Journal of Intelligent Transportation Systems, vol. 3, pp. 503-518, 2022, doi: 10.1109/OJITS.2022.3182925.
Archie J. Huang and Shaurya Agarwal, 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, vol. 4, pp. 279-293, 2023, doi: 10.1109/OJITS.2023.3268026.
Michael Muhlmeyer, Archie J. Huang and Shaurya Agarwal, Event Triggered Social Media Chatter: A New Modeling Framework, IEEE Transactions on Computational Social Systems, vol. 6, no. 2, pp. 197-207, April 2019, doi: 10.1109/TCSS.2019.2897674.
Michael Muhlmeyer, Shaurya Agarwal and Archie J. Huang, Modeling Social Contagion and Information Diffusion in Complex Socio-technical Systems, IEEE Systems Journal, vol. 14, no. 4, pp. 5187-5198, Dec. 2020, doi: 10.1109/JSYST.2020.2993542.
Pushkin Kachroo, Aaron Saiewitz, Robyn Raschke, Shaurya Agarwal and Archie J. Huang, A New Language and Hidden Markov Input/Output Model for Automated Audit Inquiry, IEEE Intelligent Systems, vol. 35, no. 6, pp. 39-49, Dec. 2020, doi: 10.1109/MIS.2019.2963653.
Pushkin Kachroo, Shaurya Agarwal, Animesh Biswas and Archie J. Huang, Nonlocal Calculus-based Macroscopic Traffic Model: Development, Analysis, and Validation. IEEE Open Journal of Intelligent Transportation Systems, vol. 4, pp. 900-908, 2023, doi: 10.1109/OJITS.2023.3335303.
Archie J. Huang and Shaurya Agarwal, Physics Informed Deep Learning for Traffic State Estimation, IEEE International Conference on Intelligent Transportation Systems, pp. 1-6, 2020, doi: 10.1109/ITSC45102.2020.9294236.
Archie J. Huang and Shaurya Agarwal, Physics Informed Deep Learning: Applications in Transportation. Submitted to Transportation in Developing Economies, Springer. Available at arXiv:2302.12336.
Archie J. Huang, Animesh Biswas and Shaurya Agarwal, Incorporating Nonlocal Traffic Flow Model in Physics-informed Neural Networks. Submitted to IEEE Transactions on Intelligent Transportation Systems. Available at arXiv:2308.11818.
Archie J. Huang, Dongdong Wang, Shaurya Agarwal, Mohamed Abdel-Aty, Md Mahmudul Islam, Muhammad Shahbaz, Physics-based Ensemble Learning for Traffic State Estimation with Variable Speed Limit. Submitted to Transportation Research Record (TRR).
Aaron Saiewitz, Robyn Raschke, Archie J. Huang, Shaurya Agarwal and Pushkin Kachroo, Using Artificial Intelligence to Detect Biased Client Statements in the Auditor-Client Inquiry Process. Submitted to The Accounting Review (TAR).
Archie J. Huang and Shaurya Agarwal, Physics Informed Deep Learning: Applications to Traffic State Estimation in Connected Vehicle Environment, 100th Transportation Research Board Annual Meeting, 2021.
Archie J. Huang and Shaurya Agarwal, Cognitive Awareness of Intelligent Vehicles: A Deep Learning Approach, Florida Automated Vehicle Summit, 2021.
Archie J. Huang and Shaurya Agarwal, Modeling and Control of V2X Enabled Traffic Streams, Florida Automated Vehicle Summit, 2019.
Archie J. Huang, Shaurya Agarwal, and Mohamed Abdel-Aty, Improving Localization Accuracy with Smartphone Sensor Data Fusion, International Conference on Smart Tourism, Smart Cities and Enabling Technology, 2019.
IEEE Transactions on Intelligent Transportation Systems (T-ITS) [3 papers].
IEEE International Intelligent Transportation Systems Conference (ITSC), 2020 [4 papers]; 2022 [1 paper].
Transportation Research Board (TRB) Annual Meeting, 2020 [1 Paper]; 2022 [1 paper].
IEEE Internet of Things Journal (IoT-J); 2023 [1 paper].
IEEE Transactions on Systems, Man, and Cybernetics (SMC) [3 papers].
IEEE Conference on Decision and Control (CDC), 2023 [1 paper].
International Federation of Automatic Control (IFAC) Symposium on Control in Transportation Systems, 2021 [2 papers].
Institution of Engineering and Technology (IET) Networks, 2024 [1 paper].
IEEE Intelligent Vehicles Symposium (IV), 2024 [1 paper].
ORCGS Doctoral Fellowship, 2018
UCF Dean’s Dissertation Completion Fellowship, 2023