Stanislav Volgushev, University of Toronto

Research

multivariate extreme value theory graphical modeling structure learning peak over threshold methods block maxima methods high dimensional statistics dependence modeling

Latest funding

Estimation and inference in extremes of high-dimensional and complex data
NSERC · 2024 · Principal investigator
$55,000
Distributional effects and computational challenges in modern data analysis
NSERC · 2017 · Principal investigator
$245,000

All 2 grants and awards

Estimation and inference in extremes of high-dimensional and complex data

Principal investigatorNSERC2024Discovery Grants Program - Individual

Principal investigators: Volgushev, Stanislav

Keywords: multivariate extreme value theory; graphical modeling; structure learning; peak over threshold methods; block maxima methods; high dimensional statistics; dependence modeling

$55,000

Distributional effects and computational challenges in modern data analysis

Principal investigatorNSERC2017Discovery Grants Program - Individual

Principal investigators: Volgushev, Stanislav

$245,000

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

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Applying for

Mention their NSERC grant from 2024

Subject: Prospective PhD student: multivariate extreme value theory Dear Professor Volgushev, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. Your research on multivariate extreme value theory connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Estimation and inference in extremes of high-dimensional and complex data" (2024), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]