At [AMD], we develop and use automated virtual materials discovery frameworks – powered by high-throughput physics-based classical and quantum calculations, artificial intelligence methods, and advanced data-infrastructures – to accelerate the discovery of molecules/materials for energy applications. My research group has highly integrated research lines that focus on the modeling of materials for energy conversion and storage, and data-driven method development, all in all to accelerate the search for good molecules/materials. We have a collaborative work culture both internally and externally with our (inter)national public and private project partners. My group is productive in developing methodological and materials research output as well as open-source codes and FAIR databases. Before joining DIFFER, I studied chemistry at Bilkent University (Turkey) and obtained PhD in physics from University of Twente (Netherlands). Subsequently, I worked as a Young Energy Scientist Fellow, first at Harvard University (USA) and then at Leiden University (Netherlands). My impact to date has been acknowledged by several monetary and computing grants, invited presentations and lectures, research prizes and a medal. I have developed and directed several small- and large-scale research projects on energy materials design that allowed me to supervise junior and senior researchers and engineers, which resulted in highly cited research publications and patents with commercial value.
Keywords: computation, chemistry, energy, materials, molecules