This archive collects past news and updates from Connor T. Jerzak, including research publications, invited talks, conference presentations, teaching, software releases, awards, and team milestones in political methodology, causal inference, machine learning, AI, and computational social science.
2025
- December 7 – Team (Markus Pettersson) presenting new work at the EurIPS 2025 workshop, CausalityImpact
- November 27 – Team (Bryan Simmons) presenting new work at the Football Collective Conference 2025
- November 19 – Team (Adel Daoud) presenting book project, Planetary Causal Inference, at Nuffield College, Oxford University
- November 5 – Nicolas Audinet de Pieuchon presenting team work, Benchmarking Debiasing Methods for LLM-based Parameter Estimates, to appear in EMNLP [Oral]
- October 27 – Guest lecture in PLA6009 – Environmental Data Analysis (Columbia University; course led by Peter Marcotullio and PhD student Kaz Sakamoto) [Slides]
- August 28 – The AY25-26 Government Department Methods Speaker Series begins! [Schedule]
- July 21 – Tutorial on Planetary Causal Inference at IC2S2 [Recording]
- May 7 – Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using EO and Computer Vision to appear at CLeaR 2025 [PDF] [Video]
- April 28 – New preprint with Priyanshi Chandra and Rishi Hazra: MiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification
- April 25 – Graduate student co-authors SayedMorteza Malaekeh and Kazuki Sakamoto presenting new work at TWEEDS [Video]
- April 24 – Congratulations to Elyse Hatch Rivera, recipient of our Excellence in Big Data Award for 2025, and to Artem Kvartalnov, recipient of the Excellence in Machine Learning Award!
- April 7 – causalimages to be presented at PolMeth Europe
- Feb 21-22 – Presenting new work at the 2025 Texas Methods Meeting (held at the University of Houston) [Paper]
- Feb 14 – Goes live: New Directions in Planetary Causal Inference
- Spring – Teaching Gov 385L (Making Big Data) [Tues 12:30-3:30 pm, BAT 5.102, Portal] and Gov 391K (Machine Learning) [Thurs 3:30-6:30 pm, BAT 5.102, Portal]
2024
- December 15 – Team (Fucheng Warren Zhu) presenting work on multi-scale dynamics in effect estimation at NeurIPS workshop, Causal Representation Learning [Video]
- December 15 – Team (SayedMorteza Malaekeh) presenting new work at NeurIPS workshop, Tackling Climate Change with Machine Learning
- December 14 – Invited talk at NeurIPS workshop, GenAI for Health: Potential, Trust and Policy Compliance
- December 9 – Graduate student co-author SayedMorteza Malaekeh presenting joint work at AGU
- December 9 – Guest lecture in PLA6009 – Environmental Data Analysis (Columbia University; course led by Peter Marcotullio and PhD student Kaz Sakamoto)
- November 15 – PlanetaryCausalInference.org, GlobalLeadershipProject.net go live
- October 25 – Presenting new work on descriptive representation at IE University (Madrid, Spain)
- October 19-24 – Presenting work on Planetary Causal Inference at the Center for Advanced Studies at Ludwig-Maximilians-Universität (LMU) (Munich, Germany)
- October 17 – Presenting new work (with graduate student Beniamino Green) at the 2024 Record Linkage Symposium, hosted by the Initiative for Data-Driven Social Science (DDSS) at Princeton University
- September 17 – Presenting new work at the GBD Science Seminar at the University of Washington [Tutorial Link]
- August 23 – Presenting new work at the Indian Institute of Management Bangalore
- July 18 – Presenting new work on measurement error under identification restrictions at Polmeth XLI [Slides]
- July 16 – New preprint on effect heterogeneity with satellite image sequences in RCTs released (joint work with PhD student Ritwik Vashistha)
- June 26 – New preprint on descriptive representation released
- June 25 – Paper on record linkage now forthcoming at PSRM
- June 21 – Team (Nicolas Audinet de Pieuchon) presenting new work on LLMs at the Sixth Workshop on NLP and Computational Social Science at NAACL [Slides] [Video]
- June 5 – Master’s students Cindy Conlin and Mikael P. Gustafsson successfully defend their theses! [PDF 1] [PDF 2]
- June 3 – New team paper, “A Scoping Review of Earth Observation and Machine Learning for Causal Inference: Implications for the Geography of Poverty”, goes live (to appear in: Hall, Ola and Ibrahim Wahab (eds.), Geography of Poverty) [Data]
- April 17 – Presenting work at the Harvard Applied Statistics Workshop
- April 16 – Presenting work on Global Causal Inference in STAT 288 – Deep Statistics: AI and Earth Observations for Sustainable Development, Statistics Department, Harvard University [Slides]
- April 4 – Presenting new work at the Midwest Political Science Association (MPSA) Conference [Slides 1] [Paper 1] [Slides 2]
- March 25 – New arXiv preprint on LLM vs. human text analysis posted, led by PhD student Nicolas Audinet de Pieuchon
- March 8 – Speaking at the Government, Public Policy, and Artificial Intelligence Conference [Slides]
- January 9 – CausalImages package now fully rebuilt with a JAX backend (4 s → 0.04 s per iteration on some hardware) and Vision Transformer backbones
- Spring – Teaching Gov 94jc (“Making Big Data”, M 12:45-2:45 pm) at Harvard University [Syllabus]
- Spring – Teaching Gov 2018 (“Introduction to Machine Learning”, W 9:45-11:45 am) at Harvard University with Naijia Liu [Course Website]
2023
- December 2 – Presenting new work at the Interactive Causal Learning Conference
- October 24 – The DescriptiveRepresentationCalculator released on CRAN
- October 12 – Presenting new work at the Data Analytics Colloquium
- August 31 – Presenting “Leveraging Satellite Images in Observational Studies of Global Development: Challenges and Opportunities” at the Methodological Advances in Causal Inference panel [Slides] [Paper] [Code]
- August 31 – Starting the graduate seminar “Statistical Analysis in Political Science” [Syllabus]
- August 17 – Presenting new work at the Rand Center for Causal Inference 2023 Symposium
- July 9 – Presenting new work at PolMeth XL
- July 7 – Giving a virtual short course, “Causal Inference with Satellite Data”, at the Society for Causal Inference [Register] [Link for Participants]
- June 21 – “The Composition of Descriptive Representation” now forthcoming at American Political Science Review [PDF] [Code]
- May 26 – Honorable Mention, Tom Ten Have Award, Society for Causal Inference [Details]
- May 24 – Presenting “Image-based Treatment Effect Heterogeneity” at the 2023 American Causal Inference Conference (ACIC) [PDF], collaborators presenting joint research, “Conceptualizing Treatment Leakage in Text-based Causal Inference” [PDF]
- May 10 – Collaborative project recognized as a Top 100 research initiative with potential for significant societal impact by the Royal Swedish Academy of Engineering Sciences [Details]
- April 26 – Presenting new work at the Center for Data and Methods (CMD) Colloquium at the University of Konstanz, Germany
- April 25 – Guest lecturing in STAT 288 – Deep Statistics: AI and Earth Observations for Sustainable Development, Statistics Department, Harvard University [Slides]
- April 13 – Presenting “Image-based Treatment Effect Heterogeneity” at CLeaR [Article PDF] [Summary PDF] [Code]
- March 3 – Presenting new work at UT Austin’s Statistics & Data Sciences Seminar
- January 9 – Started teaching the graduate seminar, “Making Big Data” [Syllabus]
- January 6 – The paper, “Image-based Treatment Effect Heterogeneity”, now forthcoming at CLeaR, PMLR [PDF] [Code]
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
- August 18 – Started as a visiting scholar in the Program on Governance and Local Development (GLD) at the University of Gothenburg, Sweden
- August 18 – Started a postdoctoral position at the AI and Global Development Lab, Linköping University, Sweden
- May 29 – Graduated from Harvard University with a Ph.D. from the Department of Government [Dissertation]
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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