Dr. Hao Jiang is an Associate Professor at the School of Mechanical and Electrical Engineering, Northeast Forestry University, China. He holds a Ph.D. in Computational Mechanics from Dalian University of Technology and specializes in laser welding, additive manufacturing, residual stress analysis, and the application of machine learning in material behavior prediction. Dr. Jiang has led and participated in numerous national and industrial research projects, including those funded by the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, and the aerospace and aircraft programs. His work addresses critical challenges in the accurate characterization and optimization of mechanical properties in welded and additively manufactured materials. His research integrates advanced simulation techniques, such as virtual field methods and thermo-mechanical coupling, with deep learning frameworks like convolutional neural networks to improve modeling accuracy and predictive performance in complex manufacturing processes. He has published nearly 30 peer-reviewed SCI papers in high-impact journals including Optics and Laser Technology, Ocean Engineering, Thin-walled Structures, and Journal of Materials Research and Technology. In addition to research, Dr. Jiang contributes to academic and professional communities. He serves as a special invited editor for multiple journals. He is also a committee member of the Chinese Society of Experimental Mechanics. Dr. Jiang is committed to interdisciplinary collaboration, particularly in the intersection of computational mechanics, materials science, and artificial intelligence, aiming to bridge fundamental research with real-world manufacturing applications.
Dr. Hao Jiang is an Associate Professor at the School of Mechanical and Electrical Engineering, Northeast Forestry University, China. He holds a Ph.D. in Computational Mechanics from Dalian University of Technology and specializes in laser welding, additive manufacturing, residual stress analysis, and the application of machine learning in material behavior prediction. Dr. Jiang has led and participated in numerous national and industrial research projects, including those funded by the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, and the aerospace and aircraft programs. His work addresses critical challenges in the accurate characterization and optimization of mechanical properties in welded and additively manufactured materials. His research integrates advanced simulation techniques, such as virtual field methods and thermo-mechanical coupling, with deep learning frameworks like convolutional neural networks to improve modeling accuracy and predictive performance in complex manufacturing processes. He has published nearly 30 peer-reviewed SCI papers in high-impact journals including Optics and Laser Technology, Ocean Engineering, Thin-walled Structures, and Journal of Materials Research and Technology. In addition to research, Dr. Jiang contributes to academic and professional communities. He serves as a special invited editor for multiple journals. He is also a committee member of the Chinese Society of Experimental Mechanics. Dr. Jiang is committed to interdisciplinary collaboration, particularly in the intersection of computational mechanics, materials science, and artificial intelligence, aiming to bridge fundamental research with real-world manufacturing applications.
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