Connor T. Jerzak
@jerzakconnor.bsky.social
@UTAustin
"Nullius in verba"
Book → planetarycausalinference.org/book-launch
Jobs → aidevlab.org/jobs
"Nullius in verba"
Book → planetarycausalinference.org/book-launch
Jobs → aidevlab.org/jobs
Pinned
"Counterfactuals. At planetary scale."
The Planetary Causal Inference (PCI) book launches soon:
planetarycausalinference.org/book-launch/
The Planetary Causal Inference (PCI) book launches soon:
planetarycausalinference.org/book-launch/
"Counterfactuals. At planetary scale."
The Planetary Causal Inference (PCI) book launches soon:
planetarycausalinference.org/book-launch/
The Planetary Causal Inference (PCI) book launches soon:
planetarycausalinference.org/book-launch/
November 17, 2025 at 2:57 PM
"Counterfactuals. At planetary scale."
The Planetary Causal Inference (PCI) book launches soon:
planetarycausalinference.org/book-launch/
The Planetary Causal Inference (PCI) book launches soon:
planetarycausalinference.org/book-launch/
Excited to see our PhD student Andrés Cruz (@arcruz0) presenting his work "Sensitivity Bounds for Uncertainty Propagation" at LAPolMeth IX in Viña del Mar, Chile.
Catch it during the poster session on Nov 22 (12:45-14:00, Building C). Don't miss this work on uncertainty in quant social science!
Catch it during the poster session on Nov 22 (12:45-14:00, Building C). Don't miss this work on uncertainty in quant social science!
November 14, 2025 at 5:23 PM
Excited to see our PhD student Andrés Cruz (@arcruz0) presenting his work "Sensitivity Bounds for Uncertainty Propagation" at LAPolMeth IX in Viña del Mar, Chile.
Catch it during the poster session on Nov 22 (12:45-14:00, Building C). Don't miss this work on uncertainty in quant social science!
Catch it during the poster session on Nov 22 (12:45-14:00, Building C). Don't miss this work on uncertainty in quant social science!
Reposted by Connor T. Jerzak
Debiasing ML predictions for causal inference—no new labels needed. We propose Tweedie’s correction to fix shrinkage enabling “one map, many trials.”
arxiv.org/abs/2508.01341
#CausalInference #MachineLearning #EarthObservation #PovertyMapping
arxiv.org/abs/2508.01341
#CausalInference #MachineLearning #EarthObservation #PovertyMapping
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis
Machine learning models trained on Earth observation data, such as satellite imagery, have demonstrated significant promise in predicting household-level wealth indices, enabling the creation of high-...
arxiv.org
August 31, 2025 at 1:21 PM
Debiasing ML predictions for causal inference—no new labels needed. We propose Tweedie’s correction to fix shrinkage enabling “one map, many trials.”
arxiv.org/abs/2508.01341
#CausalInference #MachineLearning #EarthObservation #PovertyMapping
arxiv.org/abs/2508.01341
#CausalInference #MachineLearning #EarthObservation #PovertyMapping
Reposted by Connor T. Jerzak
🥳 Join us in celebrating @alongcamejones.bsky.social and his legacy with the Policy Agendas Project. Excited to see what @seanmtheriault.bsky.social and Derek Epp do next! 🤟
November 5, 2025 at 6:01 PM
🥳 Join us in celebrating @alongcamejones.bsky.social and his legacy with the Policy Agendas Project. Excited to see what @seanmtheriault.bsky.social and Derek Epp do next! 🤟
Reposted by Connor T. Jerzak
ML wealth maps from space 🛰️ are great, but suffer from "shrinkage" bias, which waters down policy impact results (causal inference). We developed correction methods that fix this bias *without* new data.
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
November 4, 2025 at 1:30 PM
ML wealth maps from space 🛰️ are great, but suffer from "shrinkage" bias, which waters down policy impact results (causal inference). We developed correction methods that fix this bias *without* new data.
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
Reposted by Connor T. Jerzak
Are you interested in using earth observation data and deep learning for estimating poverty in Africa, poverty specifically? Then apply to this research engineer position at AI and Global Development Lab. More info about our research at www.aidevlab.org . Deadline is 7th Nov.
lnkd.in/ePX7VT-K
lnkd.in/ePX7VT-K
AI & GLOBAL DEVELOPMENT LAB - AI and Global Development Lab
The AI & Global Development Lab fuses AI with Earth Observation to illuminate the causes and consequences of human development across time and space. Our interdisciplinary team, comprising data scient...
www.aidevlab.org
November 4, 2025 at 1:31 PM
Are you interested in using earth observation data and deep learning for estimating poverty in Africa, poverty specifically? Then apply to this research engineer position at AI and Global Development Lab. More info about our research at www.aidevlab.org . Deadline is 7th Nov.
lnkd.in/ePX7VT-K
lnkd.in/ePX7VT-K
New undergrad course (UT Austin, this spring): Gov 355M - AI & Programming Foundations for Computational Social Science.
We'll treat curiosity as our raw material and AI+computation as our foundry - learning how the frontiers of technology can accelerate discovery in the social sciences + beyond.
We'll treat curiosity as our raw material and AI+computation as our foundry - learning how the frontiers of technology can accelerate discovery in the social sciences + beyond.
November 5, 2025 at 2:07 PM
New undergrad course (UT Austin, this spring): Gov 355M - AI & Programming Foundations for Computational Social Science.
We'll treat curiosity as our raw material and AI+computation as our foundry - learning how the frontiers of technology can accelerate discovery in the social sciences + beyond.
We'll treat curiosity as our raw material and AI+computation as our foundry - learning how the frontiers of technology can accelerate discovery in the social sciences + beyond.
Reposted by Connor T. Jerzak
A little less than 2 weeks to submit an abstract proposal for PolMeth - Europe. Join us in Dublin this coming May to share your new political science research using cutting edge methods!!
Submit, submit! 🚨
Pleasant reminder to all, the 5th European PolMeth meeting will be 14-15 May 2026 at Trinity College Dublin 🇮🇪
Submissions close Nov. 15 ⚠️
You can find out more about the conference, including the submission form, here: polmeth.eu
If you have any questions, please contact me 😀
Pleasant reminder to all, the 5th European PolMeth meeting will be 14-15 May 2026 at Trinity College Dublin 🇮🇪
Submissions close Nov. 15 ⚠️
You can find out more about the conference, including the submission form, here: polmeth.eu
If you have any questions, please contact me 😀
November 4, 2025 at 11:49 AM
A little less than 2 weeks to submit an abstract proposal for PolMeth - Europe. Join us in Dublin this coming May to share your new political science research using cutting edge methods!!
Reposted by Connor T. Jerzak
Check out the data paper (open access) and the publicly available data: We hope that many people will use it in their research and for other purposes.
NEW -
Paths to Power: A New Dataset on the Social Profile of Governments - https://cup.org/47i6oKQ
- @jacobnyrup.bsky.social, @chknutsen.bsky.social, @peterla.bsky.social & Ina Lyftingsmo Kristiansen
#OpenAccess
Paths to Power: A New Dataset on the Social Profile of Governments - https://cup.org/47i6oKQ
- @jacobnyrup.bsky.social, @chknutsen.bsky.social, @peterla.bsky.social & Ina Lyftingsmo Kristiansen
#OpenAccess
October 20, 2025 at 4:09 PM
Check out the data paper (open access) and the publicly available data: We hope that many people will use it in their research and for other purposes.
When on-the-ground data are scarce or outdated, satellites can keep the evidence flowing. Our guide shows how to turn data from satellites into useful causal claims, improving targeting + evaluation, avoiding common issues related to resolution mismatch / leakage / spatial dependence.
October 10, 2025 at 11:03 AM
When on-the-ground data are scarce or outdated, satellites can keep the evidence flowing. Our guide shows how to turn data from satellites into useful causal claims, improving targeting + evaluation, avoiding common issues related to resolution mismatch / leakage / spatial dependence.
Reposted by Connor T. Jerzak
Connor T. Jerzak, Adel Daoud
Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
https://arxiv.org/abs/2510.00128
Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
https://arxiv.org/abs/2510.00128
October 2, 2025 at 6:17 AM
Connor T. Jerzak, Adel Daoud
Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
https://arxiv.org/abs/2510.00128
Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
https://arxiv.org/abs/2510.00128
Reposted by Connor T. Jerzak
Adel Daoud, Cindy Conlin, Connor T. Jerzak: Chinese vs. World Bank Development Projects: Insights from Earth Observation and Computer Vision on Wealth Gains in Africa, 2002-2013 https://arxiv.org/abs/2509.25648 https://arxiv.org/pdf/2509.25648 https://arxiv.org/html/2509.25648
October 1, 2025 at 6:52 AM
Adel Daoud, Cindy Conlin, Connor T. Jerzak: Chinese vs. World Bank Development Projects: Insights from Earth Observation and Computer Vision on Wealth Gains in Africa, 2002-2013 https://arxiv.org/abs/2509.25648 https://arxiv.org/pdf/2509.25648 https://arxiv.org/html/2509.25648
Reposted by Connor T. Jerzak
LSE's Department of Methodogy is searching for an Assistant Professor in Computational Social Science. Applicants from across the social sciences are very welcome!
Please reach out if you would like any more details.
Please reach out if you would like any more details.
Assistant Professor in Computational Social Science
Assistant Professor in Computational Social Science,
,
<p style="text-align: center;"><em><span>LSE is committed to building a diverse, equitable and truly inclusive university</span></em></p>
<p styl...
jobs.lse.ac.uk
September 15, 2025 at 11:59 AM
LSE's Department of Methodogy is searching for an Assistant Professor in Computational Social Science. Applicants from across the social sciences are very welcome!
Please reach out if you would like any more details.
Please reach out if you would like any more details.
Fall schedule for the Political Methodology Seminar Series at the UT Austin Department of Government, AY25-26 is out! Event calendar links here: connorjerzak.com/methods-seri...
August 18, 2025 at 7:13 PM
Fall schedule for the Political Methodology Seminar Series at the UT Austin Department of Government, AY25-26 is out! Event calendar links here: connorjerzak.com/methods-seri...
Reposted by Connor T. Jerzak
With a new Multi-Scale Representation Concatenation method, researchers enhance satellite imagery optimization for causal inference in anti-poverty programs by revealing treatment effect heterogeneity across scales, potentially amplifying impacts without extra costs. https://arxiv.org/abs/2411.02134
Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using Earth Observation and Computer Vision: Applications to Two Anti-Poverty RCTs
ArXiv link for Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using Earth Observation and Computer Vision: Applications to Two Anti-Poverty RCTs
arxiv.org
March 18, 2025 at 12:30 PM
With a new Multi-Scale Representation Concatenation method, researchers enhance satellite imagery optimization for causal inference in anti-poverty programs by revealing treatment effect heterogeneity across scales, potentially amplifying impacts without extra costs. https://arxiv.org/abs/2411.02134
Reposted by Connor T. Jerzak
Attention #polisky! Apply for
@utaustin.bsky.social LBJ School of Public Affairs with a focus on American Political Institutions. I'm on the committee, so please reach out with questions. See below: apply.interfolio.com/170943
@utaustin.bsky.social LBJ School of Public Affairs with a focus on American Political Institutions. I'm on the committee, so please reach out with questions. See below: apply.interfolio.com/170943
Apply - Interfolio
{{$ctrl.$state.data.pageTitle}} - Apply - Interfolio
apply.interfolio.com
August 12, 2025 at 2:28 PM
Attention #polisky! Apply for
@utaustin.bsky.social LBJ School of Public Affairs with a focus on American Political Institutions. I'm on the committee, so please reach out with questions. See below: apply.interfolio.com/170943
@utaustin.bsky.social LBJ School of Public Affairs with a focus on American Political Institutions. I'm on the committee, so please reach out with questions. See below: apply.interfolio.com/170943
August 12, 2025 at 2:33 PM
Reposted by Connor T. Jerzak
Markus Pettersson, Connor T. Jerzak, Adel Daoud: Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven P... https://arxiv.org/abs/2508.01341 https://arxiv.org/pdf/2508.01341 https://arxiv.org/html/2508.01341
August 5, 2025 at 6:53 AM
Markus Pettersson, Connor T. Jerzak, Adel Daoud: Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven P... https://arxiv.org/abs/2508.01341 https://arxiv.org/pdf/2508.01341 https://arxiv.org/html/2508.01341
Reposted by Connor T. Jerzak
Markus Pettersson, Connor T. Jerzak, Adel Daoud
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis
https://arxiv.org/abs/2508.01341
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis
https://arxiv.org/abs/2508.01341
August 5, 2025 at 4:10 AM
Markus Pettersson, Connor T. Jerzak, Adel Daoud
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis
https://arxiv.org/abs/2508.01341
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis
https://arxiv.org/abs/2508.01341
Reposted by Connor T. Jerzak
Satiyabooshan Murugaboopathy, Connor T. Jerzak, Adel Daoud: Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty? https://arxiv.org/abs/2508.01109 https://arxiv.org/pdf/2508.01109 https://arxiv.org/html/2508.01109
August 5, 2025 at 6:29 AM
Satiyabooshan Murugaboopathy, Connor T. Jerzak, Adel Daoud: Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty? https://arxiv.org/abs/2508.01109 https://arxiv.org/pdf/2508.01109 https://arxiv.org/html/2508.01109
Excited to teach two grad courses @UTAustin Spring '26!
📊 Gov 385La: Making Big Data – Learn web scraping, crowd-sourcing, & data curation to build high-quality datasets for social sci impact.
🌍 Gov 385Lb: Causal ML & EO for Social Sci – Deploy satellite data & ML for causal inf at planetary scale
📊 Gov 385La: Making Big Data – Learn web scraping, crowd-sourcing, & data curation to build high-quality datasets for social sci impact.
🌍 Gov 385Lb: Causal ML & EO for Social Sci – Deploy satellite data & ML for causal inf at planetary scale
August 2, 2025 at 7:01 PM
Excited to teach two grad courses @UTAustin Spring '26!
📊 Gov 385La: Making Big Data – Learn web scraping, crowd-sourcing, & data curation to build high-quality datasets for social sci impact.
🌍 Gov 385Lb: Causal ML & EO for Social Sci – Deploy satellite data & ML for causal inf at planetary scale
📊 Gov 385La: Making Big Data – Learn web scraping, crowd-sourcing, & data curation to build high-quality datasets for social sci impact.
🌍 Gov 385Lb: Causal ML & EO for Social Sci – Deploy satellite data & ML for causal inf at planetary scale
Reposted by Connor T. Jerzak
Connor T. Jerzak, Stephen A. Jessee: Attenuation Bias with Latent Predictors https://arxiv.org/abs/2507.22218 https://arxiv.org/pdf/2507.22218 https://arxiv.org/html/2507.22218
July 31, 2025 at 6:53 AM
Connor T. Jerzak, Stephen A. Jessee: Attenuation Bias with Latent Predictors https://arxiv.org/abs/2507.22218 https://arxiv.org/pdf/2507.22218 https://arxiv.org/html/2507.22218
Join a cool group at UC Berkeley, March 7-8, 2026, for "Clouds, Streams, and Ground (Truths)"—exploring methods to study algorithmic music ecosystems. Details: www.algorithmicmusicmethods.com
Algorithmic Music Methods Conference 2026 - Clouds, Streams, and Ground (Truths)
musicology, ethnomusicology, media studies, academic conference, AI, machine learning, algorithms, critical data studies, science and technology studies
www.algorithmicmusicmethods.com
July 24, 2025 at 6:20 PM
Join a cool group at UC Berkeley, March 7-8, 2026, for "Clouds, Streams, and Ground (Truths)"—exploring methods to study algorithmic music ecosystems. Details: www.algorithmicmusicmethods.com
A First Course in Planetary Causal Inference: Confounding. Adel presents.
www.youtube.com/watch?v=oD7D...
www.youtube.com/watch?v=oD7D...
A First Course in Planetary Causal Inference: Confounding - Adel Daoud at IC2S2 2025
YouTube video by Planetary Causal Inference - Academic Content
www.youtube.com
July 22, 2025 at 12:41 PM
A First Course in Planetary Causal Inference: Confounding. Adel presents.
www.youtube.com/watch?v=oD7D...
www.youtube.com/watch?v=oD7D...
Reposted by Connor T. Jerzak
Connor T. Jerzak, Priyanshi Chandra, Rishi Hazra
Selecting Optimal Candidate Profiles in Adversarial Environments Using Conjoint Analysis and Machine Learning
https://arxiv.org/abs/2504.19043
Selecting Optimal Candidate Profiles in Adversarial Environments Using Conjoint Analysis and Machine Learning
https://arxiv.org/abs/2504.19043
April 29, 2025 at 7:23 AM
Connor T. Jerzak, Priyanshi Chandra, Rishi Hazra
Selecting Optimal Candidate Profiles in Adversarial Environments Using Conjoint Analysis and Machine Learning
https://arxiv.org/abs/2504.19043
Selecting Optimal Candidate Profiles in Adversarial Environments Using Conjoint Analysis and Machine Learning
https://arxiv.org/abs/2504.19043