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.
- Ph.D. in Industrial Engineering, University of Wisconsin - Madison - (Madison, Wisconsin, United States) 2014
- M.S. in industrial Engineering, University of Wisconsin - Madison - (Madison, Wisconsin, United States) 2012
- B.S. in Mechanical Engineering, Massachusetts Institute of Technology - (Cambridge, Massachusetts, United States) 2010
- McDonald, A. D., Ferris, T. K., & Wiener, T. A. (2020). Classification of Driver Distraction: A Comprehensive Analysis of Feature Generation, Machine Learning, and Input Measures. HUMAN FACTORS. 62(6), 1019-1035.
- Zhu, Y., Jayagopal, J. K., Mehta, R. K., Erraguntla, M., Nuamah, J., McDonald, A. D., Taylor, H., & Chang, S. (2020). Classifying Major Depressive Disorder Using fNIRS During Motor Rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 28(4), 961-969.
- Smith, A., McDonald, A. D., & Sasangohar, F. (2020). Night-shift nurses and drowsy driving: A qualitative study. International Journal of Nursing Studies. 103600-103600.
- Goddard, T., McDonald, A. D., Alambeigi, H., Kim, A. J., & Anderson, B. A. (2020). Unsafe bicyclist overtaking behavior in a simulated driving task: The role of implicit and explicit attitudes. ACCIDENT ANALYSIS AND PREVENTION. 144, 105595-105595.
- McDonald, A. D., Sasangohar, F., Jatav, A., & Rao, A. H. (2019). Continuous monitoring and detection of post-traumatic stress disorder (PTSD) triggers among veterans: A supervised machine learning approach. IISE Transactions on Healthcare Systems Engineering. 9(3), 1-15.
- Brown, T., Lee, J., Schwarz, C., Fiorentino, D., & McDonald, A. (2014). Assessing the feasibility of vehicle-based sensors to detect drowsy driving. Feasibility of Vehicle-Based Sensors to Detect Drowsy Driving and Alcohol Impairment (with accompanying CD-ROM). (pp. 1-56).
- McLaurin, E., McDonald, A. D., Lee, J. D., Aksan, N., Dawson, J., Tippin, J., & Rizzo, M. (2014). Variations on a theme. Proceedings of the Human Factors and Ergonomics Society. 58(1), 2107-2111.
- McDonald, A. D., Lee, J. D., Aksan, N. S., Dawson, J. D., Tippin, J., & Rizzo, M. (2013). Highway Healthcare. Proceedings of the Human Factors and Ergonomics Society. 57(1), 1859-1863.
- McDonald, A. D., Schwarz, C., Lee, J. D., & Brown, T. L. (2012). Real-Time Detection of Drowsiness Related Lane Departures Using Steering Wheel Angle. Proceedings of the Human Factors and Ergonomics Society. 56(1), 2201-2205.