Martin-Pierre Schmidt

Martin-Pierre Schmidt is a Lecturer at the National Institute of Applied Sciences (INSA) Rouen, affiliated with the Department of Mathematical Engineering. His research focuses on topological/multi-physics optimization, approximation theory, and applications in computer-aided geometric design (CAGD). He completed his PhD in March 2020 under the supervision of Christian Gout, with co-supervisors David Bonner and Auxkin Ortuzar from Dassault Systèmes, funded by Dassault Systèmes. His work integrates machine learning and data science into imaging and design processes.

He teaches in the GM5 program at INSA Rouen, emphasizing machine learning and data approximation techniques. His research team is part of the Numerical Analysis, Imaging and Approximation group. Notable contributions include interactive topology optimization tools, biomimetic microstructure design, and robust 3D shape detection algorithms. His thesis defense in 2020 involved a jury of international experts in mechanical engineering and computational design.

Key collaborations include Dassault Systèmes, with applications in CAD model optimization and manufacturing process design. His work bridges theoretical optimization methods with practical industrial applications in additive manufacturing and structural engineering.