Research output per year
Research output per year
Personal profile
Biography
Dr. Kai Zhou received his B.S. and M.S. in automotive engineering from Chongqing University, respectively, and received his Ph.D. degree in mechanical engineering from the University of Connecticut (UCONN). After graduation, he worked in the industry as a research engineer and then returned to academia as a postdoctoral researcher in the advanced manufacturing research group at UCONN.
Research interests
Dr. Kai Zhou has a broad research interest, ranging from structural dynamics and vibration control, structural health monitoring, prognostics and health management, smart materials and sensors, to metamaterial design and optimization. He has strong expertise in data-driven design optimization, uncertainty quantification, propagation and reliability analysis, machine learning, and modeling and simulation of multi-physics systems and processes.
Teaching
Dynamic Systems
Mechanical System Design and Analysis
Structural Mechanics
Mechanical Vibrations
Education/Academic qualification
Doctor of Philosophy, University of Connecticut
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Collaborations and top research areas from the last five years
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Research output
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A generic causality-informed neural network (CINN) methodology for quantitative risk analytics and decision support
Zhang, X., Long, X., Liu, Y., Zhou, K. & Li, J., Nov 2024, In: Risk Analysis. 44, 11, p. 2677-2695 19 p.Research output: Journal article publication › Journal article › Academic research › peer-review
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Convolutional Dimension-Reduction With Knowledge Reasoning for Reliability Approximations of Structures Under High-Dimensional Spatial Uncertainties
Shi, L., Zhou, K. & Wang, Z., 1 Jul 2024, In: Journal of Mechanical Design. 146, 7, 071701.Research output: Journal article publication › Journal article › Academic research › peer-review
3 Citations (Scopus) -
Enhanced seismic wave attenuation in graded seismic metamaterials with novel unit cells
Pan, H., Wang, Z. & Zhou, K., 9 May 2024, Active and Passive Smart Structures and Integrated Systems XVIII. Tol, S., Huang, G., Li, X., Nouh, M. A., Shahab, S. & Yang, J. (eds.). SPIE, 129460R. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 12946).Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review
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Harnessing collaborative learning automata to guide multi-objective optimization based inverse analysis for structural damage identification
Zhang, Y., Zhou, K. & Tang, J., Jul 2024, In: Applied Soft Computing. 160, 111697.Research output: Journal article publication › Journal article › Academic research › peer-review
2 Citations (Scopus) -
Inspection of Wind Turbine Blades Using Image Deblurring and Deep Learning Segmentation
Lu, J., Gao, Q. & Zhou, K., 9 May 2024, Health Monitoring of Structural and Biological Systems XVIII. Su, Z., Peters, K. J., Ricci, F. & Rizzo, P. (eds.). SPIE, 129510L. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 12951).Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review
1 Citation (Scopus)