Research Areas

Methodological work ⚙️Applications 🔬
Global causal inferenceDescriptive representation
Research designPolitical economy
Computational text analysisSocial movements & globalization
More: ConnorJerzak.com/Research

Academic Background

Primary affiliation: Assistant Professor in the Department of Government at the University of Texas at Austin

Visiting affiliation: Visiting Assistant Professor in the Department of Government at Harvard University

Consulting role: Institute for Health Metrics & Evaluation (IHME), University of Washington

Ph.D., Government, Harvard (2021)

A.M., Statistics, Harvard (2020)

[Bio] [CV] [Students]

News & Events

2024

2023

2022

  • November 7 – Presenting “Image-based Treatment Effect Heterogeneity” at the 2022 Causal Data Science Meeting
  • November 5 – Presenting “Image-based Treatment Effect Heterogeneity” at the Texas Methods (“TexMeth”) Meeting
  • September 1 – Started teaching the graduate seminar, “Machine Learning in Political Science” [Syllabus]
  • September 1 – Started teaching the graduate seminar, “Statistical Analysis in Political Science” [Syllabus]
  • August 18 – Presenting “Image-based Treatment Effect Heterogeneity” at the 2022 RAND Center for Causal Inference (CCI) Symposium
  • August 1 – Started an Assistant Professorship at the University of Texas at Austin
  • April 29 – The book chapter, “Football Fandom in Egypt”, published in Routledge Handbook of Sports in the Middle East [PDF]
  • July 17 – Received a Top 10% Reviewer Award from the International Conference on Machine Learning (ICML)
  • April 8 – The paper, “Conceptualizing Treatment Leakage in Text-based Causal Inference”, accepted at NAACL [PDF]
  • February 24 – Presenting “Learning to See Causal and Effect: Causal Inference with Images” at the Institute for Analytical Sociology, Linköping University, Sweden
  • February 21 – Presenting “The Composition of Descriptive Representation” at an ETH Zurich seminar [PDF] [Code]
  • January 7 – The paper, “An Improved Method of Automated Nonparametric Content Analysis for Social Science”, published in Political Analysis [PDF] [Code]

2021

2020

  • September 16 – Presenting “Detecting and Characterizing Latent Influence Dynamics in Social Science Data Using Machine Learning” at the Harvard Applied Statistics Workshop
  • September 13 – Presenting “Detecting and Characterizing Latent Influence Dynamics in Social Science Data Using Machine Learning” at APSA
  • July 14 – Presenting “Detecting and Characterizing Latent Influence Dynamics in Social Science Data Using Machine Learning” at PolMeth XXXVII
  • May 28 – Received an A.M. in Statistics from Harvard University
  • May 4 – The paper, “The impact of a transportation intervention on electoral politics: Evidence from E-ZPass”, published in Research in Transportation Economics [PDF] [Boston Globe Write-up]

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