Research

Scientific reports of the laboratory

• Development and theoretical analysis of new effective stochastic machine learning algorithms, 2024
• Structural learning and its applications, 2023
• Stochastic algorithms in machine learning, 2022
• Uncertainty quantification in machine learning algorithms, 2021
• Uncertainty quantification in high-dimensional models, 2020
• Uncertainty quantification in high-dimensional statistics, 2019
• Stochastic algorithms and statistical analysis of multidimensional data, 2018

Grants

• RSF grant № 19-71-30020, "Applications of probabilistic artificial neural generative models to development of digital twin technology for non-linear stochastic systems", 2019 - 2022 (HSE University)

• RSF grant № 18-11-00132, "Analysis of high dimensional random objects with applications to large-scale data processing", 2018-2020 (HSE University) grant leader: A.Naumov, PI's: V. Spokoiny, D. Belomestny

• RSF grant № 19-31-90062, "A unified view on randomized numerical methods for solving convex optimization problems", 2019 (HSE University) grant leader: A. Gasnikov, PI's: A. Tyurin

• Presidents of Russian Federation Grant for young scientists №  4596.2016.1, "Local laws for random matrices and universality of local spectral statistics", 2016-2017 (Lomonosov MSU, Skoltech)

• RFBR grant 16-31-00005 ”Spectral analysis of large dimensional random matrices”, 2016–2017 (Lomonosov MSU, Skoltech)