Generating Advances with AI for Neutrons/X-rays co-leader of WG3 (AI for knowledge)LINXS Fellow

Professor, KTH Royal Institute of Technology, Stockholm, Sweden

Ozan is a professor of mathematics at KTH Royal Institute of Technology. He is an applied mathematician who has spent the past 25 years developing theory and algorithms for large-scale ill-posed inverse problems in tomography, microscopy, and structural biology. After starting in pure mathematics, his work shifted towards computational methods driven by real-world needs in science, medicine, and industry. Since 2014, he has led KTH’s interdisciplinary Mathematical Imaging Science group, including collaborations with industrial partners to develop AI models for tomographic imaging systems, giving him deep expertise in physics-informed AI for tomography. He also led the development of the ODL software framework for inverse problems, which integrates high-performance computing libraries with deep learning tools. Ozan brings extensive leadership experience from senior roles at KTH, including strategic coordination for the Center for Industrial and Applied Mathematics (2009–2017) and leadership of KTH’s Life Science Technologies platform (2012–2018). He has a strong track record of building collaborations and launching new research directions, further strengthened by a visiting professorship at the University of Cambridge and the Alan Turing Institute (2018–2019). In addition, he has worked for over 15 years in R&D in Swedish industry, in areas ranging from financial risk control and biomedical imaging to computational software.