Phillip L. Morgan
Papers
5
Total Citations
35
H-Index
3
About
Phillip L. Morgan is a researcher at the forefront of human factors engineering, with key contributions in fatigue detection, human-robot collaboration, and autonomous vehicle interaction. His work addresses critical challenges in Industry 4.0 and 5.0, focusing on how technology can monitor, mitigate, and recover from human physical and cognitive fatigue. Morgan’s most cited paper (2024, 23 citations) provides a comprehensive review of machine learning methods for fatigue detection, highlighting the gap in personalized performance monitoring. He has pioneered the use of synthetic datasets generated by deep learning models to analyze physical fatigue in collaborative robot environments, a novel approach that reduces reliance on costly real-world data collection. His research also explores the psychological dimensions of automation, notably examining the benefits and pitfalls of anthropomorphizing autonomous vehicle assistants during accidents—a study with implications for public trust and user acceptance. Through his work on cobots and human-centric workplace design, Morgan is shaping safer, more adaptive industrial systems. With a growing citation record and contributions spanning 2023–2025, his interdisciplinary approach bridges machine learning, ergonomics, and human-computer interaction, making him a notable voice in the future of human-automation collaboration.
Research Focus
Key Achievements
Top Papers
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