Faculty Profile for Dr. Tao Ma

profile photo for Dr. Tao Ma
Dr. Tao Ma
Lecturer — Ingram School of Engineering
IGRM 2102
phone: (512) 245-1826
Scholarly/Creative Work
Service

Biography Section

Biography and Education

 Dr. Tao Ma is a lecturer of the Ingram School of Engineering at Texas State University. He received his Ph.D. and M.A.Sc. in transportation systems engineering from University of Toronto, Canada. He was a postdoc lecturer and project team lead in Technical University of Munich and postdoc research fellow in The University of Texas at Austin before joining Texas State University. His research interests are in network-level traffic flow prediction, transportation systems modeling, simulation, optimization, calibration, and machine learning, statistical methods, data science.

Teaching Interests

 Courses currently taught:
Operations Research (IE3340)
Engineering Statistics (IE3320)
Probabilistic Operations Research (IE4370)
Statistical Design of Experiments (IE4310/5310)

Master's level courses taught:
Statistical Learning and Data Analytics
Applied Statistics
Discrete (Probabilistic) Choice Methods
Urban Operations Research
Optimization
ITS Architecture and Applications

Research Interests

 Statistics and probability, machine learning, operations research, optimization, data analytics, time series forecasting, functional data analysis, and dimension reduction techniques
Network-level traffic state prediction, transportation systems modeling, simulation, and calibration, traffic flow operations and management, demand forecast, urban mobility

Selected Scholarly/Creative Work

  • Ma, T., Yao, F., & Zhou, Z. (2024). Network-Level Traffic Flow Prediction: Functional Time Series vs. Functional Neural Network Approach. The Annals of Applied Statistics, Vol. 18(1), 424–444. https://doi.org/10.1214/23-AOAS1795
  • Chen, H., Yan, X., Liu, X., & Ma, T. (2022). Exploring the operational performance discrepancies between online ridesplitting and carpooling transportation modes based on DiDi data. Transportation, Springer Nature. https://doi.org/10.1007/s11116-022-10297-6
  • Zhu, Y., Qurashi, M., Ma, T., & Antoniou, C. (2021). Joint Calibration for DTA Model Using Islands-GA and PC-SPSA. Transportation Research Procedia, 52, 716–723. https://doi.org/10.1016/j.trpro.2021.01.086
  • Fatola, A., Ma, T., & Antoniou, C. (2021). Modeling and Forecasting Individual On-Demand Upcoming Trips. The 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), IEEE Xplore. https://doi.org/10.1109/MT-ITS49943.2021.9529314
  • Hamad, S. Y. Y., Ma, T., & Antoniou, C. (2021). Analysis and Prediction of Bikesharing Traffic Flow – Citi Bike, New York. The 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), IEEE Xplore. https://doi.org/10.1109/MT-ITS49943.2021.9529290

Selected Service Activities

Reviewer / Referee
Transportation Research Part A: Policy and Practice
July 2023-July 2023
Reviewer / Referee
Sensors
July 2023-July 2023
Reviewer / Referee
Expert Systems With Applications
May 2023-May 2023
Reviewer / Referee
Springer Nature ¬ Transportation
May 2023-May 2023
Reviewer / Referee
Transportation Research Part B: Methodological
December 2016-May 2023