Welcome to my website! I am a Banting postdoctoral researcher in the Department of Political Science at Columbia University. At Columbia, I work with Donald Green.
Broadly speaking, I am interested in voting behaviour, political representation, public opinion, legislative politics, women & politics, partisanship and political methodology.
My research projects use a variety of quantitative methods. I employ observational data, experiments, as well as causal inference designs. Before Columbia, I earned my PhD in the Department of Political Science from l’Université de Montréal and my Honours BA and MA from the University of Toronto.
My dissertation, What Voters Want: Identifying Voter Preferences for Candidates, examines voters decisions of whom to support. In doing so, I focus on the following candidate characteristics: gender, age, occupation and incumbency. To address these questions, I built an original database of candidate-level observations for elections since 1867 in Canadian federal elections–the largest collection of this kind (downloaded on Dataverse over 3,000 times). The database includes variables for unique id (which standardizes candidates names across time), names of candidates, riding names, unique identification number for each riding, province, date of birth, gender, occupation, occupation categories, party affiliation, party categories, switchers, incumbency status, vote shares, raw votes, indigenous origins, candidates who identify as a member of the LGBTQ2+ community and so on. Here is more information about the data. You can find my dissertation here, which is comprised of six articles. As of February 2022, all the articles of my dissertation are published in the Canadian Journal of Political Science, Electoral Studies, Legislative Studies Quarterly, American Review of Canadian Studies and as a book chapter.
*If you are a first-generation student applying to political science Ph.D. programs or Canadian funded postdocs (e.g. Banting, SSHRC, FRQSC), I would be more than happy to discuss and give comments on your materials.