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Technische Universität München

Tao Ma

Postdoctoral Lecturer, Project Team Leader

Dr. Ma was a postdoctoral lecturer at Technical University of Munich from 2018 to 2022. He taught 5 courses for the program of Master of Science in transportation systems, and supervised master students’ theses and co-supervised Ph.D. students. He was the project team leader for the project of Monitoring, Modeling and forecasting Mobility patterns (MO3). Dr. Ma has extensive research experience in machine learning, statistical time series forecast, big data analytics, and microscopic simulation of transportation systems. His interdisciplinary research spans spatial-temporal urban mobility modeling, forecast and statistical methodology. His research articles can be found on the journals of Transportation Research Part B, IEEE Transactions on Intelligent Transportation Systems (ITS), Transportation Research Record, etc. He also has many years of consulting experience in transportation engineering industry.

Research Interests

  • Modeling and simulation of transportation systems, ITS, Urban mobility modeling and forecast
  • Network traffic state prediction, Traffic operations and management, Public transit
  • Statistical and machine learning, Big data analytics, Heuristic optimization
  • Time series modeling, Functional data analysis, Advanced forecast methods

Selected Publications

  • Tao Ma, Constantinos Antoniou, Tomer Toledo (2020) Hybrid machine learning algorithm and statistical time series model for network-wide traffic forecast, Transportation Research Part C: Emerging Technologies, Volume 111 Pages 352–372, doi.org/10.1016/j.trc.2019.12.022
  • Moeid Qurashi, Tao Ma, Emmanouil Chaniotakis, and Constantinos Antoniou (2019) PC–SPSA: Employing Dimensionality Reduction to Limit SPSA Search Noise in DTA Model Calibration, IEEE Transactions on Intelligent Transportation Systems, doi.org/10.1109/TITS.2019.2915273
  • Tao Ma, Zhou Zhou, Constantinos Antoniou (2018) Dynamic Factor Model for Network Traffic State Forecast, Transportation Research Part B: Methodological, Volume 118, Pages 281-317 doi.org/10.1016/j.trb.2018.10.018
  • Tao Ma, Constantinos Antoniou, Tomer Toledo (2018) Combination of Neural Network and statistical model for network-wide traffic forecast. Traffic Flow Theory and Characteristics Midyear Meeting, Woods Hole, Massachusetts, USA, 7-9 August 2018
  • M. Qurashi, T. Ma, E. Chaniotakis, C. Antoniou, (2018) An Alternate Online Calibration approach for O-D demand Calibration in Dynamic Traffic Assignment Systems, 7th Symposium of the European Association for Research in Transportation - hEART2018 Athens, Greece, 5-7 September 2018
  • M. Qurashi, T. Ma, E. Chaniotakis, C. Antoniou, (2018) PC-SPSA: Employing dimensionality reduction to limit SPSA noise in DTA model calibration, 2nd Symposium on Management of Future motorway and urban Traffic Systems, Ispra, June 11-12, 2018
  • Tao Ma, Zhou Zhou, Baher Abdulhai (2016) Time series based hourly traffic flow prediction on the Greater Toronto Area freeway network, Proceedings for the joint annual CTRF/TRF conference, Toronto, Ontario, May 2016.
  • Tao Ma, Zhou Zhou, Baher Abdulhai (2015) Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction, Transportation Research Part B Methodological Volume 76, Pages 27–47 doi.org/10.1016/j.trb.2015.02.008
  • Stephen Keen, Tao Ma, Stephen Sargeant (2008) Microscopic Simulation of a Roundabout - A reality test, comparison of simulation results with observed traffic behavior. The TRB Roundabout Conference, Kansas City
  • Tao Ma and Baher Abdulhai (2002) Genetic Algorithm-Based Optimization Approach and Generic Tool for Calibrating Traffic Microscopic Simulation Parameters, Transportation Research Record: Journal of the Transportation Research Board, 1800, pp. 6-15.
  • Tao Ma, Baher Abdulhai (2001) Genetic algorithm-based combinatorial parametric optimization for the calibration of microscopic traffic simulation models, IEEE Intelligent Transportation Systems Proceedings, conference on August 25~29, 2001 Oakland, (CA), USA

Education

  • Ph.D.,  University of Toronto, Canada
  • M.A.Sc., University of Toronto, Canada
  • B.Eng. Xi’an University of Architecture & Technology, China 

Work Experience

  • Project Manager, Traffic Planning & Operations, HDR Corporation (Toronto, Canada)
  • Transportation Engineer, AECOM Canada (Whitby, Ontario, Canada)
  • Transportation Engineer, SNC-Lavalin Engineers & Constructors (Toronto, Canada) 

Teaching Activity

Course Lecturer at Technical University of Munich

  • BGU4736, Statistical Learning and Data Analytics for Transportation Systems, (2019S, 2018S)
  • BGU4811, Urban Operations Research for Transportation Systems, (2019S)
  • BGU0390, Applied Statistics in Transport, (2018/19W)
  • BGU4329, Discrete Choice Methods for Transportation Systems Analysis, (2018/19W)
  • BGU3721, Optimization for Transportation Systems, (2018S)
  • Project Seminar (2018/19W): Providing Mobility Solutions for a Rapidly Growing Munich Region

Teaching Assistant at University of Toronto

  • Transport-II Performance, CIV332H1
  • Engineering Economics, CME368H1
  • Urban Operations Research, CIV355H1
  • Engineering Mathematics II, CME362H1
  • Transport-I Introduction to Urban Transportation Systems, CIV331H1

Reviewing Activities

  • Journal of Transportation Research Part B
  • Transportation Letters: The International Journal of Transportation Research
  • Proceedings of the Institution of Civil Engineers Journal: Transport
  • Transportation Research Procedia, mobil.TUM2018
  • IET Intelligent Transport Systems
  • Advances in Transportation Studies (ATS): An International Journal
  • International Journal of Modelling and Simulation
  • hEART 2018 – 7th Symposium of the European Association for Research
  • ABE20 committee, Transportation Economics, Transportation Research Board
  • Journal of Scientia Iranica
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