• Corrie and Jim Furber '64 Faculty Fellow
  • Assistant Professor
Tony McDonald

Educational Background

  • Ph.D. Industrial Engineering, University of Wisconsin-Madison, Madison, WI, 2014
  • M.S. Industrial Engineering, University of Wisconsin-Madison, Madison, WI, 2012
  • B.S. Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 2010

Research Interests

  • Dr. McDonald's research focuses on applying machine learning to relevant problems in human factors in the transportation and healthcare domains. Specifically he is interested in using knowledge generated from machine learning algorithms to improve existing models of human behavior and improving machine learning algorithm performance by combining traditional approaches with novel data analysis and domain expertise.

Industry Experience

  • Oracle Corporation, 2014-2017

Awards & Honors

  • HFES Alphonse Chapanis Best Student Paper Award 2012
  • HFES Surface Transportation Technical Group Best Student Paper Award 2012
  • HFES Surface Transportation Technical Group Best Student Paper Award 2014

Selected Publications

  • McDonald, A.D., Ferris, T.K., and Wiener, T.A. (2019). Classification of driver distraction: A comprehensive analysis of feature generation, machine learning, and input measures. Human Factors: The Journal of the Human Factors and Ergonomics Society. https://doi.org/10.1177/0018720819856454.
  • McDonald, A.D., Sasangohar, F., Jatav, A., and Rao, A. (2019). Continuous Monitoring and Detection of Post-Traumatic Stress Disorder (PTSD) Triggers Among Veterans: A Supervised Machine Learning Approach. IISE Transactions on Health Systems Engineering. https://doi.org/10.1080/24725579.2019.1583703.
  • McDonald, A.D., Alambeigi, H., Engstr ̈om, J., Markkula, G., Vogelpohl, T., Dunne, J., and Yuma, N. (2019). Towards computational simulations of behavior during automated driving take-overs: A review of the empirical and modeling literatures. Human Factors: The Journal of the Human Factors and Ergonomics Society, 61(4).
  • McDonald, A.D., Lee, J. D., Schwarz, C., and Brown, T. L. (2018). A contextual and temporal algorithm for driver drowsiness detection. Accident Analysis and Prevention, 113(C), 25–37.
  • McDonald, A.D., Lee, J.D., Schwarz, C., and Brown, T.L. (2014). Steering in the random forest: Ensemble learning based detection of drowsiness related lane departures. Human Factors: The Journal of the Human Factors and Ergonomics Society, 56(5), 986-998.