Alexey has expertise in numerical methods, mathematical statistics and usage of data analysis in applications. In 2012, Alexey graduated from the Department of Control and Applied Mathematics of Moscow Institute of Physics and Technology (MIPT). In his Master’s thesis Alexey proposed a modification of Bayesian approach for linear regression that allows an automated feature selection. He then entered a PhD student program at the Institute for Information Transmission Problems. Alexey obtained a new result in effectiveness of Bayesian procedures for Gaussian process regression. Then he obtained a first ever theoretical justification for selection of design of experiments for variable fidelity models as well as minimax errors for Gaussian process regression in the multivariate case. His research was published in a number of peer-reviewed journals and top-ranked conferences such as AISTATS.
During his studies at MIPT Alexey joined a Skolkovo resident company DATADVANCE and took part in the development of MACROS library dedicated to data analysis for engineers. He developed a first ever industry-level tool for data fusion that solves a regression problem for the case of data with more than one fidelity. Alexey have also completed a number of projects connected with application of data analysis in Aerospace engineering and adjacent areas for such companies as AREVA, TOTAL and Airbus.
Now Alexey focuses his research on the development of a new generation of methods for processing of molecular modeling data using Machine Learning, he also participate in various industrial projects and teaching routines.