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Dr. Šulc’s research focuses on applications of statistical physics and computer modeling to the study of complex systems. He works on the development of coarse-grained models of RNA and DNA to study their biophysical properties, as well as processes involving DNA and RNA in biological or nanotechnological settings. These models allow for efficient simulations of systems consisting of up to thousands of nucleotides and have been applied to a variety of problems, ranging from the study of strand displacement and operation of an artificial DNA motor to DNA hybridization kinetics and folding of an RNA pseudo-knot. Dr. Šulc has further worked on smart-grid optimization and developed control algorithms that minimize losses and improve voltage stability in circuits with photovoltaic sources of energy. He has also studied random walks on sparse random graphs, applications of belief propagation to graph partitioning problems, and evolutionary dynamics of RNA secondary structures. Recently, he has extended his interests to olfaction and protein self-assembly.