Dr. Haijie Wang | Mechanical Structural Integrity | Research Excellence Award
East China University of Science and Technology | China
Dr. Haijie Wang is a mechanical engineering researcher specializing in AI-driven structural integrity for advanced materials and additive manufacturing. His work focuses on fatigue life prediction, machine learning, and physics-informed modeling for 3D-printed metal components. He has published 29 journal papers, many as first author, and received 976 citations from 704 documents, with an h-index of 16. His contributions include patented methods and software tools for fatigue analysis and predictive modeling. Dr. Wang has earned multiple academic honors and continues advancing intelligent engineering systems.
Citation Metrics (Scopus)
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Citations
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h-index
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Featured Publications
Traditional Machine Learning and Deep Learning for Predicting Melt-Pool Cross-Sectional Morphology of Laser Powder Bed Fusion Additive Manufacturing with Thermographic Monitoring
– Journal of Intelligent Manufacturing, 2025
Machine Learning-Based Fatigue Life Prediction of Laser Powder Bed Fusion Additively Manufactured Hastelloy X via Nondestructively Detected Defects
– International Journal of Structural Integrity, 2025
Multi-Physics Information-Integrated Neural Network for Fatigue Life Prediction of Additively Manufactured Hastelloy X Superalloy
– Virtual and Physical Prototyping, 2024
Machine Learning-Assisted Acoustic Emission Monitoring for Track Formability Prediction of Laser Powder Bed Fusion
– Materials Today Communications, 2024
Uncertainty-Aware Fatigue-Life Prediction of Additively Manufactured Hastelloy X Superalloy Using a Physics-Informed Probabilistic Neural Network
– Reliability Engineering & System Safety, 2024
Haijie Wang | Mechanical Structural Integrity | Research Excellence Award