Profile

Darko Zibar received the M.Sc. degree in telecommunication and the Ph.D. degree in optical communications from the Technical University of Denmark, in 2004 and 2007, respectively. He was a Visiting Researcher with the Optoelectronic Research Group (Prof. John E. Bowers), University of California, Santa Barbara, CA, USA, in 2006 and 2008, where he worked on coherent receivers for analog optical links. In 2009, he was a Visiting Researcher with Nokia-Siemens Networks, where he worked on clock recovery techniques for polarization multiplexed systems. He is currently group leader of Machine Learning in Photonic Systems (MLiPS) and Associate Professor at DTU Fotonik, Technical University of Denmark. His research efforts are currently focused on the application of machine learning methods to optical communication, ultra-sensitive amplitude and phase detection, quantum meatrology and optical fibre sensing systems. He is a recipient of Young Researcher Award by University of Erlangen-Nurnberg, in 2016, for his contributions to applications of machine learning techniques to optical technologies. He was a part of the team that won the HORIZON 2020 prize for breaking the optical transmission barriers. In 2017, he was granted European Research Council (ERC) Consolidator Grant where the focus is on the demonstration of nonlinear-distortion free optical communication systems using machine learning techniques