Research

Areas of Research

• Quantification of uncertainty in estimation of covariance matrices and their spectral projectors; applications of efficient dimension reduction
• Community detection and clustering
• Topological data analysis
• Data analysis based on Monge-Kantorovich spaces geometry
• Inference for discretely observed stochastic processes
• Uncertainty quantification and variance reduction for MCMC algorithms
• Statistical inference for McKean-Vlasov-SDEs

Scientific reports of the laboratory

• Uncertainty quantification in machine learning algorithms, 2021
• Uncertainty quantification in high-dimensional models, 2020
• Uncertainty quantification in high-dimensional statistics, 2019

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

• 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)