Xu Xu

Assistant Professor

Prior to joining the NC State faculty, Xu Xu started his career as a postdoctoral research fellow in the School of Public Health at Harvard University. From there he became a research scientist in Liberty Mutual Research Institute for Safety where he received best-paper and outstanding scientific contribution award multiple times.

His research interests are generally in the areas of biomechanical modeling, optimization, simulation and data mining with respect to human daily activities to promote workplace and at-home injury prevention and driving safety. Xu has published more than 40 journal articles on the aforementioned research topics. He has also served as a research advisor for three postdoctoral research fellows.

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Ph.D. 2008

Doctor of Philosophy in Industrial Engineering

NC State University

MSIE 2006

Master of Science in Industrial Engineering

NC State University

BSIE 2004

Bachelor of Science in Industrial Engineering

Tsinghua University

Research Description

Human factors and ergonomics engineering, occupational biomechanics, optimization-based biomechanical modelling, data mining on human motion data, occupational musculoskeletal injury prevention.


A Deep Neural Network-based method for estimation of 3D lifting motions
Mehrizi, R., Peng, X., Xi, Xu, Z., & Shaoting, L. (2019), JOURNAL OF BIOMECHANICS, 84, 87–93. https://doi.org/10.1016/j.jbiomech.2018.12.022
Occupational cranking operations: The scapula perspective
Lin, J.-H., & Xu, X. (2019), APPLIED ERGONOMICS, 75, 129–133. https://doi.org/10.1016/j.apergo.2018.09.011
Predicting 3-D Lower Back Joint Load in Lifting: A Deep Pose Estimation Approach
Mehrizi, R., Peng, M., Xi, Dimitris N., X., Xu, Z., & Shaoting, L. (2019), IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 49(1), 85–94. https://doi.org/10.1109/THMS.2018.2884811
Identification of heel strike under a slippery condition
Chang, W. R., & Xu, X. (2018), Applied Ergonomics, 66, 32–40.
Impact of posture choice on one-handed pull strength variations at low, waist, and overhead pulling heights
Yu, D., Xu, X., & Lin, J. H. (2018), International Journal of Industrial Ergonomics, 64, 226–234.
New technologies in human factors and ergonomics research and practice
Lin, J. H., Kirlik, A., & Xu, X. (2018), Applied Ergonomics, 66, 179–181.
Toward Marker-free 3D Pose Estimation in Lifting: A Deep Multi-view Solution
Mehrizi, R., Peng, Xi, Tang, Z., Xu, X., Metaxas, D., & Li, K. (2018), In PROCEEDINGS 2018 13TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE & GESTURE RECOGNITION (FG 2018) (pp. 485–491). https://doi.org/10.1109/FG.2018.00078
Using a deep learning network to recognise low back pain in static standing
Hu, B., Kim, C., Ning, X., & Xu, X. (2018), ERGONOMICS, 61(10), 1374–1381. https://doi.org/10.1080/00140139.2018.1481230
A computer vision based method for 3D posture estimation of symmetrical lifting
Mehrizi, R., Peng, X., Xu, X., Zhang, S. T., Metaxas, D., & Li, K. (2018), Journal of Biomechanics, 69, 40–46.
Using a marker-less method for estimating L5/S1 moments during symmetrical lifting
Mehrizi, R., Xu, X., Zhang, S. T., Pavlovic, V., Metaxas, D., & Li, K. (2017), Applied Ergonomics, 65, 541–550.

View all publications via NC State Libraries