Aukosh Jagannath, University of Waterloo

Research

High-dimensional statistics Data Science Glass transition Phase transitions Spin glasses Statistical to Algorithmic Gaps stochastic analysis variational methods

Latest funding

Mathematical Foundations of Data Science
NSERC · 2022 · Principal investigator
$240,000
Glass transitions and algorithmic barriers in high-dimensional energy landscapes
NSERC · 2020 · Principal investigator
$12,500
Glass transitions and algorithmic barriers in high-dimensional energy landscapes
NSERC · 2020 · Principal investigator
$165,000

All 3 grants and awards

Mathematical Foundations of Data Science

Principal investigatorNSERC2022Canada Research Chairs

Principal investigators: Jagannath, Aukosh

Keywords: high-dimensional statistics; machine learning; random optimization problems; mathematical foundations of data science; stochastic approximations; markov processes; Probability theory; Monte Carlo methods; neural networks

$240,000

Glass transitions and algorithmic barriers in high-dimensional energy landscapes

Principal investigatorNSERC2020Discovery Launch Supplement

Principal investigators: Jagannath, Aukosh

$12,500

Glass transitions and algorithmic barriers in high-dimensional energy landscapes

Principal investigatorNSERC2020Discovery Grants Program - Individual

Principal investigators: Jagannath, Aukosh

Keywords: spin glasses; phase transitions; statistical to algorithmic gaps; glass transition; high-dimensional statistics; stochastic analysis; variational methods; data science

$165,000

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 2022

Subject: Prospective PhD student: High-dimensional statistics Dear Professor Jagannath, 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 high-dimensional statistics 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 "Mathematical Foundations of Data Science" (2022), 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]