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Dazhong Wu

Dazhong Wu

Assistant Professor

Email: dazhong.wu@ucf.edu
Phone: 407-823-1561
Office: ENG I, Room 347

Dazhong Wu is an assistant professor in mechanical and aerospace engineering at UCF. Prior to joining UCF, Wu was a senior research associate in the Department of Industrial and Manufacturing Engineering at Penn State University. He received his B.S. from Hunan University, his M.S. from Shanghai Jiao Tong University in China, and his Ph.D. from Georgia Tech, all in mechanical engineering.

Wu has published papers in the Journal of Manufacturing Science and Engineering, the Journal of Intelligent Manufacturing, Computer-Aided Design, the Journal of Manufacturing Systems, the Journal of Computing and Information Science in Engineering, Reliability Engineering and System Safety. He serves as a NAMRI/SME Scientific Committee member. He has served as a guest managing editor for the Journal of Manufacturing Systems and the International Journal of Computer Integrated Manufacturing.

  • Data-driven prognostics and health management
  • Artificial intelligence-enabled smart manufacturing
  • Additive manufacturing
  • Engineering design
  • Obsolescence risk management and product lifecycle forecasting
  • Li, Z., Zhang, Z., Shi, J., & Wu, D.(2019). Prediction of Surface Roughness in Extrusion-based Additive Manufacturing with Machine Learning, Robotics and Computer-Integrated Manufacturing, 57:488-495.
  • Li, Z., Wu, D.,& Yu, T. (2019). Prediction of Material Removal Rate for Chemical Mechanical Planarization Using Decision Tree-Based Ensemble Learning, Transactions of the ASME, Journal of Manufacturing Science and Engineering, doi: 10.1115/1.4042051.
  • Li, Z., Goebel, K., & Wu, D.(2019). Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning, Transactions of the ASME, Journal of Engineering for Gas Turbines and Power, doi: 10.1115/1.4041674.
  • Wu, D., Wei, Y., & Terpenny, J. (2018). Predictive Modeling of Surface Roughness in Fused Deposition Modeling Using Data Fusion, International Journal of Production Research, doi: 10.1080/00207543.2018.1505058.
  • Wu, D.& Xu, C. (2018). Predictive Modeling of Droplet Formation Processes in Inkjet-Based Bioprinting, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 140(10), pp. 101007, doi: 10.1115/1.4040619.
  • Wu, D., Ren, A., Zhang, W., Fan, F., Liu, P., Fu, X., & Terpenny, J. (2018). Cybersecurity for Digital Manufacturing, Transactions of the SME,Journal of Manufacturing Systems.
  • Wang, J., Ma, Y., Zhang, L., Gao, R., & Wu, D.(2018). Deep Learning for Smart Manufacturing: Methods and Applications, Transactions of the SME, Journal of Manufacturing Systems.
  • Li, Z., Wu, D., Hu, C, & Terpenny, J. (2018). An Ensemble Learning-based Prognostic Approach with Degradation-Dependent Weights for Remaining Useful Life Prediction, Reliability Engineering and System Safety.
  • Sam Nunn Fellowship, MacArthur Foundation
  • American Society of Mechanical Engineering
  • Society of Manufacturing Engineers
  • Institute of Electrical and Electronics Engineers
  • EML 3500: Design and Analysis of Machine Components
  • EML 4327: Digital Manufacturing