معرفی
Jesper Byggmästar is an Academy Postdoctoral Researcher at the University of Helsinki, affiliated with the Department of Physics under the Faculty of Science. His research focuses on computational materials physics, particularly radiation damage mechanisms, interatomic potential development, and the behavior of advanced materials in extreme environments.
His work spans topics such as machine learning-driven simulations of materials like tungsten, gallium oxide, and high-entropy alloys, with applications in nuclear fusion and aerospace engineering. Key contributions include studies on radiation resistance, defect evolution, and interatomic potential optimization for metallic systems.
Byggmästar leads the OCRAMLIP project (2023–2027), which explores refractory alloys using machine learning, and participates in the Finnish Center for Artificial Intelligence (FCAI) flagship program. His research emphasizes bridging atomic-scale simulations with macroscopic material behavior, addressing challenges in fusion reactor materials and structural integrity under irradiation.
