Mohammad Malekan is an Associate Professor at the SDU Mechatronics (CIM) within the Institute of Mechanical and Electrical Engineering at the University of Southern Denmark. His research spans computational solid mechanics, fatigue and fracture mechanics, tribology, additive manufacturing, and structural integrity of metallic/composite materials. Research Focus: Additive manufacturing (L-PBF, FDM), finite element modeling (FEM/XFEM), material characterization, surface roughness optimization, and defect propagation in metallic structures. Scientific Contributions: Over 61 publications with expertise in fatigue analysis of titanium components, thermal load modeling in machining, and fracture mechanics of 3D-printed alloys. Awards: Recipient of the Marie Skłodowska-Curie Individual Postdoc Fellowship, Distinguished PhD Thesis award (2018), and multiple postdoctoral scholarships. Collaborations: Active in European Mechanics Society, Ingeniørforeningen (IDA), and international projects on additive manufacturing and structural repair. Recent Research Trends: Focus on laser powder bed fusion (L-PBF) of 316L stainless steel and Inconel 625, investigating microstructure-mechanical property correlations, post-heat treatment effects, and porosity analysis using X-ray nanotomography. His work also addresses tool wear optimization, friction effects in machining, and multi-scale modeling of defects in additive-manufactured components. Scientific Awards: Marie Skłodowska-Curie Postdoc Fellowship (2019) Distinguished PhD Thesis (2018) Postdoctoral Fellowships (2017) Four-year PhD Scholarship (2013) Teaching & Supervision: Supervised Master’s theses on topology optimization of additively manufactured parts and teaches courses in finite element methods, experimental solid mechanics, and advanced mechanical engineering topics. Labs & Teams: Leads research projects on fatigue analysis of additively manufactured titanium components and mechanical properties of metallic parts. Collaborates with international institutions on structural health monitoring and computational modeling.






