About me

I am a PhD student in the Cornell Brooks School of Public Policy. I hold an MSc in Inequalities and Social Science from the London School of Economics and a BA in Psychology from the University of Winnipeg. I also worked as a research analyst and product manager at Multi Health Systems Inc., as a Data Science for Social Good Fellow at the University of Washington’s eScience Institute in 2020, and a machine learning engineer at Graphika from May to November of 2021.

I am interested in a lot of things. Here is what I’ve thought about most lately:

Timeline

Now

  • Wrapping up papers for submission
  • Working on `Who moves during recessions?’ for presentation at APPAM in March
  • Starting new projects/collaborations! Fun!

06/2021 - 12/2021: Summer and fall third year

  • Worked as a Machine Learning Engineer at Graphika, building NLP classification models and models for cross-platform clustering of social media data.
  • RA for Dr. Matthew Hall on statistical models for the use of consumer data to measure population levels and migration flows.
  • Wrote my second year paper, using machine learning to improve race-ethnicity imputation.

01/2021 - 05/2021: Spring of second year

  • Awarded SSHRC Doctoral Fellowship, which will fund the next three years of my PhD! Thanks, Canada!
  • Presented a poster entitled “Small Area Population Estimates from Consumer Data” (joint with Arthur Acolin and Matthew Hall) at the PAA 2021 annual conference
  • Also presented the above at the APPAM 2021 Student Seminar Series
  • Submitted the first paper of my PhD, collaborative work with my DSSG colleagues on measuring racially polarized voting and the racial composition of the voting population.
  • TA’d Big Data for Policy Analysis

09/2020 - 12/2020: Fall of second year

  • Assembled my committee: Professors Doug Miller (Chair), Michael Macy, and Matthew Hall
  • TA’d Introduction to Statistics for PAM Majors
  • Presented ongoing research with my DSSG colleagues at PRIEC

06/2020 - 08/2020: Data Science for Social Good

  • Developed an R package to quantify vote dilution in US elections
  • Met many inspiring people
  • Learned a lot. Some highlights:
    • The “human-centered design” approach to data science
    • How to collaborate on a coding project with a team spread across North America
    • The intricacies of voting rights litigation and empirical research on voting
    • Applied Bayesian statistics and spatial analysis in R

09/2019 - 05/2020: First year at Cornell

  • Took courses in economics, statistics, computer science, sociology, and demography
  • Started contributing to some ongoing research projects
  • Became an affiliate of the Cornell Population Center (CPC)
  • Moved back to Canada when the pandemic forced classes online in March

06/2019 - 08/2019: Free summer

  • Visited friends in Berlin, road-tripped through Italy
  • Got engaged!
  • Traveled with my fiancee through South America:
    • Fancy hotel in Cartegena
    • Snorkeling on the Galapagos Islands
    • Five day hike to Machu Picchu
    • Drove through the Bolivian Salt Flats

09/2017 - 05/2019: Multi Health Systems

  • Did data science and product development research on a small “intrepreneurial” team called the Innovation Hub
  • Moved to product management:
    • Developed a business plan for a workplace mental health assessment product
    • Led a small team to help clients connect to the product’s API

09/2016 - 08/2017: London School of Economics

  • Took courses in sociology, political science, demography, and causal inference
  • Met some amazing people from all over Europe and the rest of the world
  • Took weekend trips to Croatia, Scotland, Barcelona
  • First exposure to R, and to programming (addicted ever since)
  • Presented at the European Association of Social Psychology Conference in Granada, Spain

09/2012 - 09/2016: University of Winnipeg

  • Studied political psychology in an undergraduate research lab
  • Wrote a book chapter and a text analysis paper