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
azizhusain@k-state.edu

Professional experience

Dr. Husain Aziz is an assistant professor of civil engineering at Kansas State University and leads the Transportation Infrastructure and Systems (TIS) research lab focusing on the modeling, simulation, and optimization of traffic flows in smart cities, shared-used mobility, and resilient transportation systems. Dr. Aziz co-leads the transportation infrastructure theme of the ARISE (Adaptive and Resilient Infrastructures Driven by Social Equity) project funded by the National Science Foundation (https://nsfepscor.ku.edu/track-1-arise/). He received his M.S. and Ph.D. from the University of Texas at Austin and Purdue University in 2010 and 2014, respectively, and his B.Sc. degree from Bangladesh University of Engineering and Technology in 2007. Before joining K-State Civil Engineering, Dr. Aziz held an R&D scientist position at the Oak Ridge National Laboratory of the U.S. Department of Energy (2014 – 2019). He also serves as the associate editor of the IEEE Transactions on Intelligent Transportation Systems and the Journal of Intelligent Transportation Systems (Taylor & Francis). He is a full member of the ASCE, ITE, and IEEE.

Research

Dr. Aziz's current research centers around modeling, simulation, and optimization of transportation systems. On-going externally funded projects include:

  1. Kansas NSF EPSCoR--ARISE]: Leading the resilient transportation infrastructure theme and building post-disaster recovery routing and pre-positioning algorithms accounting for equity dimensions in the decision-making.
  2. Kansas Department of Transportation—Wireless Charging of Electric Vehicles: Exploring the road electrification potentials through synthesizing the costs, benefits, infrastructure needs, and adoption rates; Developing connected vehicle applications for safety, mobility, and environmental benefits; Traffic safety focusing on rural crashes in Kansas.
  3. FHWA Pooled Fund—Autonomous Maintenance Technology: Developing decision-making tool for Autonomous Truck Mounted Attenuator technologies deployment accounting for weather, network geometry, and traffic flow variations.

We also focus on emerging mobility issues—curbside management and micromobility—in different dimensions, including energy impacts, user adoption, and modeling at different scales—macro and microscopic simulation approaches.

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),
    pp.192-204.
  • 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.