Summary
Filip Kilibarda is a research-focused engineer with a decade of experience bridging theoretical physics, nanotechnology and computational AI. After a doctorate in nanotechnology and roles at HZDR, he now serves as a Research Fellow at the Nikola Tesla Institute, applying rigorous scientific methods to practical innovation. He brings deep proficiency in Python and C++ and specialises in convolutional neural networks and computer vision, currently exploring generative models. His background in molecular-scale device research informs a unique perspective on hardware-aware computation and data-intensive problem solving. An active coder, he publishes projects like FlexVAE on GitHub that showcase his blend of research-grade rigor and hands-on AI development. Based in Belgrade, he combines academic depth with a pragmatic drive to turn complex theory into working systems.
10 years of coding experience
Doctor rerum naturalium, Physics, Doctor rerum naturalium, Physics at University of Konstanz
Physics, Physics at Technische Universität Dresden
Master of Science - MS, Theoretical and Experimental Physics, Master of Science - MS, Theoretical and Experimental Physics at University of Belgrade, Faculty of Physics
English, Serbian, Russian, German