Igor works on unraveling protein structure-dynamics-function relationship with the focus on transport tunnels. Capstone goal of his thesis is to develop a machine learning model capable of predicting protein tunnels from static structure – skipping computationally expensive simulations. In his work, he also applies Markov state models in order to estimate kinetic properties of ligand transport. He enjoys creating overcomplicated Python scripts and struggling with software compilation.