Ivan is interested in problems arising in financial mathematics, machine learning for dependent datastreams and statistical learning theory. During his Applied Mathematics MSc studies he focused on the implementation and theoretical analysis of isonormal processes and also on applying the fundamentals of learning theory for deep neural networks. He cooperates with several PhD students and researchers to develop accurate and robust estimators for fractal noise driven stochastic processes and efficient data generating algorithms for the quality learning procedures. Currently, he works at the Alfréd Rényi Institute of Mathematics as a part of the Financial Mathematics Research Group and in the ELTE AI Research Group. Ivan supervised theses concerned the topics of forcasting prices with parametric models at the Mathematics Expert in Data Analytics and Machine Learning postgraduate specialization program.