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Computer Science

D-Index
42
Citations
8686
World Ranking
8296
National Ranking
3557

Overview

Dazhong Wu is a researcher affiliated with the University of Central Florida in the United States, with a focus on engineering disciplines. Their work spans multiple subfields including mechanical engineering, automotive engineering, control and systems engineering, electrical and electronic engineering, and biomedical engineering.

The core areas of Wu's research involve additive manufacturing and 3D printing technologies, additive manufacturing materials and processes, advanced battery technologies research, machine fault diagnosis techniques, advancements in battery materials, reliability and maintenance optimization, and cellular and composite structures.

Wu has published extensively, with a total of 125 research outputs categorized under engineering. Major publication venues include:

  • Materials & Design
  • Reliability Engineering & System Safety
  • Advanced Engineering Informatics
  • SSRN Electronic Journal
  • Mechanical Systems and Signal Processing

Their research collaborations often involve the following frequent co-authors:

  • Qingyang Liu
  • Yupeng Wei
  • Janis Terpenny
  • Junchuan Shi
  • Denizhan Yavaş

Recent papers authored or co-authored by Wu highlight applications of advanced machine learning and manufacturing techniques in engineering contexts:

  • Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks, 2021, Mechanical Systems and Signal Processing
  • Prediction of melt pool temperature in directed energy deposition using machine learning, 2020, Additive Manufacturing
  • Interlaminar shear behavior of continuous and short carbon fiber reinforced polymer composites fabricated by additive manufacturing, 2020, Composites Part B Engineering
  • Prediction of state of health and remaining useful life of lithium-ion battery using graph convolutional network with dual attention mechanisms, 2022, Reliability Engineering & System Safety
  • Battery health management using physics-informed machine learning: Online degradation modeling and remaining useful life prediction, 2022, Mechanical Systems and Signal Processing

Best Publications

  • Deep learning for smart manufacturing: Methods and applications

    Jinjiang Wang;Yulin Ma;Laibin Zhang;Robert X. Gao

  • Cloud-based design and manufacturing

    Dazhong Wu;David W. Rosen;Lihui Wang;Dirk Schaefer

  • Cloud manufacturing: Strategic vision and state-of-the-art☆

    Dazhong Wu;Matthew John Greer;David W. Rosen;Dirk Schaefer

  • A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

    Dazhong Wu;Connor Jennings;Janis Terpenny;Robert X. Gao

  • Prediction of surface roughness in extrusion-based additive manufacturing with machine learning

    Zhixiong Li;Ziyang Zhang;Junchuan Shi;Dazhong Wu

  • A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing

    Dazhong Wu;Shaopeng Liu;Li Zhang;Janis Terpenny

  • Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks

    Junchuan Shi;Dikang Peng;Zhongxiao Peng;Ziyang Zhang

  • TOWARDS A CLOUD-BASED DESIGN AND MANUFACTURING PARADIGM: LOOKING BACKWARD, LOOKING FORWARD

    Dazhong Wu;J. Lane Thames;David W. Rosen;Dirk Schaefer

  • Enhancing the Product Realization Process With Cloud-Based Design and Manufacturing Systems

    Dazhong Wu;J. Lane Thames;David W. Rosen;Dirk Schaefer

  • Cybersecurity for digital manufacturing

    Dazhong Wu;Anqi Ren;Wenhui Zhang;Feifei Fan

  • An ensemble learning-based prognostic approach with degradation-dependent weights for remaining useful life prediction

    Zhixiong Li;Dazhong Wu;Chao Hu;Janis P. Terpenny

  • Prediction of melt pool temperature in directed energy deposition using machine learning

    Ziyang Zhang;Zhichao Liu;Dazhong Wu

  • Cloud-Based Manufacturing: Old Wine in New Bottles?

    Dazhong Wu;David W. Rosen;Lihui Wang;Dirk Schaefer

  • Fracture behavior of 3D printed carbon fiber-reinforced polymer composites

    Denizhan Yavas;Ziyang Zhang;Qingyang Liu;Dazhong Wu

  • Predictive modelling of surface roughness in fused deposition modelling using data fusion

    Dazhong Wu;Yupeng Wei;Janis P. Terpenny

  • Cloud Manufacturing: Drivers, Current Status, and Future Trends

    Dazhong Wu;Matthew J. Greer;David W. Rosen;Dirk Schaefer

  • Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning

    Zhixiong Li;Kai Goebel;Kai Goebel;Dazhong Wu

  • Predictive Modeling of Droplet Formation Processes in Inkjet-Based Bioprinting

    Dazhong Wu;Changxue Xu

  • Cloud-Based Design and Manufacturing: Status and Promise

    Dazhong Wu;David W. Rosen;Dirk Schaefer

  • Forecasting Obsolescence Risk and Product Life Cycle With Machine Learning

    Connor Jennings;Dazhong Wu;Janis Terpenny

  • DISTRIBUTED COLLABORATIVE DESIGN AND MANUFACTURE IN THE CLOUD — MOTIVATION, INFRASTRUCTURE, AND EDUCATION

    Dirk Schaefer;J Lane Thames;Robert D Wellman;Dazhong Wu

Frequent Co-Authors

David W. Rosen
David W. Rosen Singapore University of Technology and Design
Robert X. Gao
Robert X. Gao Case Western Reserve University
Kai Goebel
Kai Goebel Palo Alto Research Center
Soundar R. T. Kumara
Soundar R. T. Kumara Pennsylvania State University
Thomas R. Kurfess
Thomas R. Kurfess Oak Ridge National Laboratory
Lihui Wang
Lihui Wang Royal Institute of Technology
Chao Hu
Chao Hu Iowa State University
Yongho Sohn
Yongho Sohn University of Central Florida
Peng Wang
Peng Wang Nanyang Technological University
Albert J. Shih
Albert J. Shih University of Michigan–Ann Arbor

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