Stephen Vavasis, University of Waterloo

Research

Algorithms Computational mechanics Convex relaxation Data science Machine learning Optimization

Latest funding

Convex relaxation of problems in data science and efficient solution methods
NSERC · 2020 · Principal investigator
$225,000
Theory and Applications of Nonnegative Matrix Factorization
NSERC · 2013 · Principal investigator
$150,000
Preconditioning for linear systems arising in modeling and optimization
NSERC · 2007 · Principal investigator
$130,000

All 3 grants and awards

Convex relaxation of problems in data science and efficient solution methods

Principal investigatorNSERC2020Discovery Grants Program - Individual

Principal investigators: Vavasis, Stephen

Keywords: optimization; data science; convex relaxation; algorithms; machine learning; computational mechanics

$225,000

Theory and Applications of Nonnegative Matrix Factorization

Principal investigatorNSERC2013Discovery Grants Program - Individual

Principal investigators: Vavasis, Stephen

$150,000

Preconditioning for linear systems arising in modeling and optimization

Principal investigatorNSERC2007Discovery Grants Program - Individual

Principal investigators: Vavasis, Stephen

$130,000

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

Write to this professor

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Applying for

Mention their NSERC grant from 2020

Subject: Prospective PhD student: Algorithms Dear Professor Vavasis, 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 algorithms 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 "Convex relaxation of problems in data science and efficient solution methods" (2020), 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]