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Civil Engineering

Husain Aziz | Assistant Professor

Photo of Mustaque Hossian

Ph.D. - 2014, Purdue University - West Lafayette
Transportation and Infrastructure Systems Engineering
M.S. - 2009, The University of Texas Austin
Transportation Engineering
B.Sc. - 2007, Bangladesh University of Engineering and Technology
Civil Engineering

Contact Information

2132 Fiedler Hall

Professional Experience

Husain Aziz received his doctoral degree from Purdue University-West Lafayette with a concentration in transportation infrastructure and systems engineering. Before joining the civil engineering department at K-State in 2019, Aziz held a staff R&D scientist position at the Oak Ridge National Laboratory, or ORNL. He was the lead principal investigator of several energy efficient mobility systems, or EEMS, projects sponsored by the Vehicle Technologies Office of the U.S. Department of Energy. Aziz is a member of the Institute of Transportation Engineers and an associate member of the American Society of Civil Engineers, or ASCE. 


Aziz’s primary areas of expertise include (a) transportation modeling and simulation — high-performance agent-based simulation, dynamic traffic assignment and network control in a connected and automated environment; (b) optimization of road infrastructure operations and management under extreme events — assessing vulnerability and identifying critical components; and (c) machine learning and econometric models using data from connected-vehicle environments, traffic crashes and driving studies. At K-State, Aziz will lead the INC3S INtelligent Computing for Safe, Smart, and Sustainable — Lab with core focuses on the modeling, simulation and control of mixed traffic of human and autonomous vehicles in smart cities, shared-used mobility modeling and optimization, and resilient transportation systems.

The INC3S lab currently seeks motivated doctoral students and Interested applicants should share a recent CV (include standard test scores and courses taken) and summary of research accomplishments and focus areas (not more than two pages) with Aziz (azizhusain@k-state.edu). 

Academic Highlights

Husain has co-authored one book chapter, and several peer-reviewed journal and conference proceedings papers. He received a Superior Performance Award and Distinguished Contribution Recognition at ORNL. He and his colleagues from the National Renewable Energy Laboratory also received the best poster award at the 2018 ASCE Transportation and Development Institute conference. Aziz serves as a peer-reviewer for several SJR Q1 journals and as a grant proposal reviewer for different funding agencies.

Recent Faculty Publications
  • Guo, Q., Ban, X.J. and Aziz, H. M. A., 2021. Mixed traffic flow of human-driven vehicles and automated vehicles on dynamic transportation networks. Transportation Research Part C: Emerging Technologies, 128, p.103159.
  • Akter, S. and Aziz, H. M. A., 2021. Effectiveness of Automated Connected Shuttles (ACS) During COVID-19 Pandemic. 14th International Workshop on Computational Transportation Science (IWCTS 2021), November 1, 2021, Beijing, China. (https://doi.org/10.1145/3486629.3490694)
  • Aziz, H. M. A. and Islam, H., 2021. A Data-driven Framework to Identify Human-Critical Autonomous Vehicle Testing and Deployment Zones. 14th International Workshop on Computational Transportation Science (IWCTS 2021), November 1, 2021, Beijing, China. (https://doi.org/10.1145/3486629.3490692)
  • Aziz, H. M. A., Garikapati, V., Rodriguez, T.K., Zhu, L., Sun, B., Young, S.E. and Chen, Y., 2020. An optimization-based planning tool for on-demand mobility service operations. International Journal of Sustainable Transportation, pp.1-12.
  • H. Wang, S. V. Patil, H. M. A. Aziz and S. Young, "Modeling and Control Using Stochastic Distribution Control Theory for Intersection Traffic Flow," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 1885-1898, March 2022, doi: 10.1109/TITS.2020.3028994.
  • Al Islam, S.M.A. Bin, Ali Hajbabaie, H.M. A. Aziz, A real-time network-level traffic signal control methodology with partial connected vehicle information, Transportation Research Part C: Emerging Technologies, Volume 121, 2020, 102830, https://doi.org/10.1016/j.trc.2020.102830.
  • Aziz, H. M. A. and D. M. Banisakher (2020), Operational interdependency between electrical substations and road networks under extreme events, 2020 IEEE International Smart Cities Conference (ISC2), Piscataway, NJ, USA, 2020, pp. 1-8, doi: 10.1109/ISC251055.2020.9239097.
  • Xu, X., Aziz, H. M. A., Liu, H., Rodgers, M. O., & Guensler, R. (2020). A scalable energy modeling framework for electric vehicles in regional transportation networks. Applied Energy, 269, 115095. https://doi.org/10.1016/j.apenergy.2020.115095
  • Al Islam, S. B., Aziz, H. M. A., & Hajbabaie, A. (2020). Stochastic Gradient-Based Optimal Signal Control With Energy Consumption Bounds. IEEE Transactions on Intelligent Transportation Systems.  doi: 10.1109/TITS.2020.2979384.
  • Aziz, H. M. A., Park, B.H., Morton, A., Stewart, R.N., Hilliard, M. and Maness, M. A high-resolution agentbased model to support walk-bicycle infrastructure investment decisions: A case study with New York City. Transportation research part C: emerging technologies, 86, pp.280-299.
  • Aziz, H. M. A., Zhu, F., Ukkusuri, S. V. Learning-based traffic signal control algorithms with neighborhood
    information sharing: An application for sustainable mobility. Journal of Intelligent Transportation
    Systems, 22(1), 40-52.
  • Aziz, H.M.A., and Ukkusuri, S.V. A novel approach to estimate emissions from large transportation
    networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES
    using dynamic time warping measures. International Journal of Sustainable Transportation, 12(3),
  • Islam, SMA. B. Al, H. M. A. Aziz, H. Wang, and S. E. Young. Minimizing energy consumption from
    connected signalized intersections by reinforcement learning. 2018 IEEE Intelligent Transportation
    Systems Conference (ITSC).
    Park, B. H., H. M. A. Aziz, A. Morton, and R. Stewart. High performance Data Driven Agent-based
    Modeling Framework for Simulation of Commute Mode Choices in Metropolitan
    Area. 2018 IEEE Intelligent Transportation Systems Conference (ITSC).
  • Zhu, Lei, Venu Garikapati, Yuche Chen, Yi Hou, H. M. A. Aziz, and Stanley Young. Quantifying the Mobility
    and Energy Benefits of Automated Mobility Districts Using Micro-scopic Traffic Simulation. In
    proceedings of ASCE International Conference on Transportation and Development Institute, 2018.
  • Park, B. H., Aziz, H. M. A., Morton, A., Stewart, R. N. A novel graph partitioning technique for highperformance agent-based simulation of travel mode choices. Paper no. 18-05808. In the proceedings of the Transportation Research Board 97th Annual Meeting, Washington, D. C., January 7-11, 2018.