Xu Xu
Assistant Professor
- 919.513.7205
- xxu@ncsu.edu
- 484 Daniels Hall
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.
Meet Xu Xu: ISE Welcomes New Faculty
Visit the Biomechanics Lab
Education
Doctor of Philosophy in Industrial Engineering
NC State University
Master of Science in Industrial Engineering
NC State University
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.
Publications
- 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.