Stanislav was born in Moscow in 1983 and moved with his parents to Germany at the age of 6. He studied Mathematics at the Ruhr University Bochum and received his diploma (equivalent of MSc) in 2007 and his PhD in 2010, both under the supervision of Holger Dette. He stayed in Bochum until 2015 as postdoctoral researcher, with a one-year visit in 2012 to the University of Illinois at Urbana-Champaign as visiting scholar with Roger Koenker and Stephen Portnoy. He joined Cornell University as Assistant Professor in 2015 and moved to Toronto in 2016. Here, he was promoted to Associate Professor in 2022.

Stanislav has a total of 48 publications, many appearing in the leading journals of our discipline,  including the Annals of Statistics (AoS) (8 publications), the Journal of the Royal Statistical Society (JRSSB), (4 publications) and the Journal of the American Statistical Association (JASA) (3 publications). 

In his diploma and PhD, Stanislav worked on quantile regression, and he has continued this line of research throughout his career. In his widely cited 2019 Annals of Statistics paper (joint with Guang Cheng and Shi-Kang Chao), Stanislav proposed the first approach to quantile regression for very large data sets utilizing the divide-and-conquer approach and not only established guarantees for the success of divide and conquer procedures but also exhibited scenarios where divide and conquer procedures provably fail. Stanislav also made significant contributions to quantile regression for panel data with Jiaying Gu. In his 2020 Journal of Econometrics publication with Jiaying Gu and Antonio Galvao, Stanislav established new results on the limiting distribution of quantile regression when many individual specific effects are estimated simultaneously, by proving that previously known rates in this problem were much too pessimistic. Stanislav also made ingenious methodological contributions to panel data quantile regression with grouped individual effects, using a merging penalty to automatically group fixed effect estimators (Gu and Volgushev, Journal of Econometrics, 2019) and applied spectral clustering ideas in an innovative paper (Yu, Gu and Volgushev, Journal of Econometrics, 2024).

Stanislav has also worked on several other aspects of dependence modeling. His work on Hadamard differentiability of the copula map (Bücher, Volgushev, JMVA, 2013), convergence in weak metrics under mild smoothness assumptions (Bücher, Segers, Volgushev, AoS 2014), and weak convergence with respect to stronger weighted metrics (Berghaus, Bücher, Volgushev, Bernoulli 2017) provide key tools for the analysis of rank-based procedures. Another line of Stanislav’s work, joint with Marc Hain, Holger Dette and Tobias Key, combines the power of copulas with frequency domain methods in time series to obtain procedures which can describe time series dynamics such as tail dependence and asymmetric behaviour in time that evade classical correlation-based methods. 

Many of Stanislav’s recent contributions are to extreme value analysis. As with much of his other work, he combines methodological innovation with thorough theoretical guarantees to tackle questions including the dichotomy between asymptotic independence and dependence (Lalancette, Engelke, Volgushev, AoS 2021), tree structure learning (Engelke, Volgushev, JRSSB 2022) and learning flexible graphical models for extremes (Engelke, Lalancette, Volgushev, AoS 2026).

Stanislav enjoys discussions with his colleagues and collaborating on fun theory problems. This has led to joint publications on bootstrap procedures, high-dimensional change-pint detection and functional time series. His recent preprints consider various topics including causal inference, high-dimensional functional data, benign overfitting, and non-parametric maximum likelihood.

He also greatly enjoys working and learning together with trainees. During his time at the University of Toronto four PhD students have completed their degrees under his (co-)supervision. Three of them are now in tenure track positions at City University Hong Kong, Université du Québec à Montréal and Rice University, and one is postdoc at Ruhr University Bochum. Stanislav also supervised one postdoc who has a tenure track position at Macquarie University in Australia. He is currently supervising four PhD students and one Postdoc.

He has contributed to the Department of Statistical Sciences by serving as associate chair for graduate studies and to the wider profession as associate editor for several journals, including Bernoulli (past) and the Electronic Journal of Statistics (current), the Canadian Journal of Statistics (current) and Extremes (current).

Stanislav is deeply grateful to his parents Maxim Volgushev and Marina Chistyakova and brother Nikolaj Volgushev for support and inspiration, his wife Jiaying Gu for her support, infinite patience and many collaborations, and his daughter Vera for the joy she brings to his life. He is also grateful to his supportive colleagues at the University of Toronto. He has benefitted greatly from working with wonderful PhD students, postdocs and collaborators. 

Outside of work, Stanislav enjoys time with his family, photography, and competitive fishing with his wife at which he gets beaten every time.