Feng Dai, University of Alberta

Research

Applied functional Analysis Cubature formulas, discrepancy, and energy-minimizing High-dimensional approximation Orthogonal polynomial expansions Polynomial inequalities Sampling discretization Function spaces high dimensional approximation

Latest funding

Sampling discretization and approximation in high-dimensional spaces
NSERC · 2023 · Principal investigator
$25,000
Sampling discretization, cubature formulas and quantitative approximation in multidimensional settings
NSERC · 2020 · Principal investigator
$162,000
Cubature Formulas, Orthogonal Expansions and Quantitative Approximation on Regular Domains
NSERC · 2015 · Principal investigator
$125,000

All 5 grants and awards

Sampling discretization and approximation in high-dimensional spaces

Principal investigatorNSERC2023Alliance Grants

Principal investigators: Dai, Feng F

Keywords: Function spaces; high dimensional approximation; high dimensional probability; sampling discretization and recovery

$25,000

Sampling discretization, cubature formulas and quantitative approximation in multidimensional settings

Principal investigatorNSERC2020Discovery Grants Program - Individual

Principal investigators: Dai, Feng

Keywords: cubature formulas, discrepancy, and energy-minimizing; sampling discretization; high-dimensional approximation; polynomial inequalities; applied functional analysis; orthogonal polynomial expansions

$162,000

Cubature Formulas, Orthogonal Expansions and Quantitative Approximation on Regular Domains

Principal investigatorNSERC2015Discovery Grants Program - Individual

Principal investigators: Dai, Feng

$125,000

Orthogonal expansions, cubature formulas and approximation in several variables

Principal investigatorNSERC2010Discovery Grants Program - Individual

Principal investigators: Dai, Feng

$120,000

Approximation of functions on compact manifolds and positivity of polynomial

Principal investigatorNSERC2005Discovery Grants Program - Individual

Principal investigators: Dai, Feng

$50,000

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 2023

Subject: Prospective PhD student: Applied functional Analysis Dear Professor Dai, 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 applied functional analysis 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 "Sampling discretization and approximation in high-dimensional spaces" (2023), 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]