معرفی
Paul Green is a Lecturer II in the Department of Statistics at the University of Michigan, affiliated with the College of Literature, Science, and the Arts. He earned his Ph.D. in Biostatistics from the same university in 1995. His research focuses on Bayesian data analysis, categorical data analysis, and applications in transportation systems. Key areas include driver behavior analysis, human factors in automotive interfaces, and emotion recognition via EEG signals.
Education:
- Ph.D. in Biostatistics, University of Michigan, 1995
Research Interests:
- Bayesian statistical methodologies
- Driver cognitive load and fatigue
- Autonomous vehicle decision-making
- EEG-based emotion recognition
- Human factors in transportation safety
Recent publications emphasize driver-brain interactions in high-speed rail environments, autonomous vehicle lane-change strategies using deep reinforcement learning, and tactile intervention systems for fatigue mitigation. His work bridges biostatistics with engineering, particularly in automotive human factors and simulation technologies.
No scientific awards or grants are explicitly listed. No advisee students are recorded in the provided materials. His research extends to interdisciplinary topics like lifestyle mobilities of aging populations and standardization of driver evaluation protocols.
