Dr. Howard Chen
Assistant Professor
Biography
Howard Chen is an Assistant Professor for the Industrial & Systems Engineering and Engineering Management (ISEEM) department at UAH. Dr. Chen’s research interests broadly span the areas of Robotics, Navigation, Biomechanics, and Occupational Ergonomics, where he focuses on (i) the navigation of vehicles and pedestrians, (ii) the development of control systems for wearable robotics, and (iii) the development and application of wearable sensors for biomechanical motion analysis. Much of his work leverages multi-sensor data fusion, state estimation, machine learning, and miniature MEMS-based gyroscopes, accelerometers, and magnetometers. Prior to joining UAH, Dr. Chen was a Postdoctoral Fellow and Assistant Research Professor for the Department of Mechanical Engineering at Auburn University working primarily within the GPS & Vehicle Dynamics Lab (GAVLAB). Dr. Chen received his Ph.D. in Industrial Engineering at The University of Iowa, where he was a NIOSH Fellow and a Graduate Research Assistant within the Department of Occupational and Environmental Health.
Curriculum Vitae
Education
- Ph.D., Industrial Engineering, The University of Iowa, 2017
- M.S., Industrial Engineering, The University of Iowa, 2012
- B.S., Mechanical Engineering, The University of Iowa, 2010
Expertise
- Occupational Ergonomics
- Wearable Sensors
- Robotics
- Navigation
- Human Factors/Ergonomics
- Biomechanical Motion Analysis
- Sensor Fusion/Optimal State Estimation
- Machine Learning
- Inertial Sensors
Recent Publications
Chen, H., Schall Jr, M. C., Fethke, N. B. (2023) Gyroscope Vector Magnitude: A proposed method for measuring angular velocities. Applied Ergonomics, (in-press)
Schall Jr, M. C., Chen, H., & Cavuoto, L. (2022). Wearable inertial sensors for objective kinematic assessments: a brief overview. Journal of Occupational and Environmental Hygiene, 19(9), 501-508.
Zhang, X., Schall Jr, M. C., Chen, H., Gallagher, S., Davis, G. A., & Sesek, R. (2022). Manufacturing worker perceptions of using wearable inertial sensors for multiple work shifts. Applied Ergonomics, 98, 103579.
Schall Jr, M. C., Zhang, X., Chen, H., Gallagher, S., & Fethke, N. B. (2021). Comparing upper arm and trunk kinematics between manufacturing workers performing predominantly cyclic and non-cyclic work tasks. Applied Ergonomics, 93, 103356.
Coker, J., Chen, H., Schall Jr, M. C., Gallagher, S., & Zabala, M. (2021). EMG and joint angle-based machine learning to predict future joint angles at the knee. Sensors, 21(11), 3622.