Luiza Antonie, University of Guelph

Research

bias data integration data mining machine learning record linkage

Latest funding

Bias and Representativeness in Linked Data
NSERC · 2020 · Principal investigator
$144,000
Data unification for customer profile generation
NSERC · 2019 · Principal investigator
$25,000
Quantitative aspects of well-being and inequality in British settler societies, 1850-1920
SSHRC · 2017 · Co-investigator
$148,374

All 5 grants and awards

Bias and Representativeness in Linked Data

Principal investigatorNSERC2020Discovery Grants Program - Individual

Principal investigators: Antonie, Luiza

Keywords: data integration; record linkage; bias; data mining; machine learning

$144,000

Data unification for customer profile generation

Principal investigatorNSERC2019Engage Grants Program

Principal investigators: Antonie, Luiza

$25,000

Quantitative aspects of well-being and inequality in British settler societies, 1850-1920

Co-investigatorSSHRC2017Insight Grants

Principal investigators: Inwood, Kris E.

Keywords: well-being; historical origins; anthropometric; standard of living; living; comparative; Indigenous; ethnicity; colonialism

$148,374

Rethinking the Canadian homestead era: the case from Alberta, 1871-1916

Co-investigatorSSHRC2016Insight Grants

Principal investigators: Baskerville, Peter A.

Keywords: social history; population movement; settlement; economy; migration; western history; big data

$175,510

Record Linkage Across Heterogeneous Data Sources

Principal investigatorNSERC2014Discovery Grants Program - Individual

Principal investigators: Antonie, Luiza

$138,000

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 2020

Subject: Prospective PhD student: bias Dear Professor Antonie, 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 bias 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 "Bias and Representativeness in Linked Data" (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]