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Mohammad Mianroodi is a distinguished mechanical engineer and materials scientist, known for his extensive research and contributions in the field of mechanical engineering and materials science. He completed his Ph.D. at the University of Strasbourg, France, where he specialized in the experimental and numerical determination of forming limit diagrams (FLDs) using biaxial and Nakajima tests, with industrial applications in deep drawing simulations for FCC and BCC metals. His dissertation was highly regarded for its innovative approach and practical implications in the industry.
Mianroodi's academic journey also includes a Master's degree in Mechanical Engineering and Computational Engineering from the University of Strasbourg, where he conducted a Finite Element Study of a wrist prosthesis.
Post-Ph.D., Mianroodi continued his research as a Postdoctoral Research Fellow in Paris, France. His work focuses on the development and application of physics-informed neural networks for the analysis of nonlinear structures, showcasing his proficiency in both theoretical and practical aspects of mechanical engineering.
Mianroodi's professional skills extend to numerous numerical and computational tools, including ABAQUS, COMSOL, ANSYS, CATIA, SolidWorks, and Hypermesh, among others. He is also proficient in programming languages such as Python, MATLAB, and FORTRAN. His experimental skills include digital image correlation, X-ray crystallography, digital volume correlation, and various manufacturing and design techniques.
His publications, which include studies on wrist prosthesis, forming limit diagrams for various materials, and the application of physics-informed neural networks, reflect his commitment to advancing knowledge and technology in his field. Mohammad Mianroodi's contributions to mechanical engineering and materials science are marked by a blend of in-depth research, practical application, and continuous innovation.