theaidevlab/WorldDev.2026.1073278
Updated
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8
AI & ML interests
We're creating a causal atlas of global well-being---combining satellite imagery, AI agent swarms, traditional machine learning, and causal methods to track and test human development at scale
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Papers
Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
Chinese vs. World Bank Development Projects: Insights from Earth Observation and Computer Vision on Wealth Gains in Africa, 2002-2013
cjerzak
published
a
dataset
2 days ago
Post
681
Ethos: In our team at UT Austin, we train students to become full-stack researchers—and increasingly, designers of the systems that do research. Our students learn to carry projects end-to-end: from idea generation and theory to data creation, analysis, and iterative refinement across diverse subfields. Using modern AI (including agentic workflows) and scalable computation, students build reproducible pipelines that can ingest and update planetary-scale data—like satellite imagery and other high-dimensional sources. But the goal isn’t tool use for its own sake: students learn to set the objectives, constraints, and evaluation standards that guide these systems through large spaces of hypotheses, while grounding results in causal inference and careful measurement. The outcome is scholarship that can rigorously test policy counterfactuals and translate evidence into durable, responsible improvements in societal well-being.
We welcome students at every stage to engage with projects—from motivated high-schoolers to undergraduates, graduate students, and those from highly non-traditional backgrounds.
Join us! https://connorjerzak.com/students/
We welcome students at every stage to engage with projects—from motivated high-schoolers to undergraduates, graduate students, and those from highly non-traditional backgrounds.
Join us! https://connorjerzak.com/students/
- 2 replies
cjerzak
authored
2
papers
23 days ago
cjerzak
updated
a
Space
2 months ago
Post
2878
>>> We're writing a new book, <Planetary Causal Inference>, on how to model counterfactuals at planetary scale by combining satellite imagery + other global data with local studies and RCTs. Forthcoming in 2026+.
>>> Book info: https://planetarycausalinference.org/book-launch
>>> All datasets used in the book will be openly available on our lab’s Hugging Face hub:
theaidevlab
>>> Book info: https://planetarycausalinference.org/book-launch
>>> All datasets used in the book will be openly available on our lab’s Hugging Face hub:
cjerzak
authored
2
papers
4 months ago
Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
Paper
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2510.00128
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Published
Chinese vs. World Bank Development Projects: Insights from Earth Observation and Computer Vision on Wealth Gains in Africa, 2002-2013
Paper
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2509.25648
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Published
Post
277
Excited to share LinkOrgs Online, a web app hosted here on HF for embedding and linking organization names using character-level Transformer encoder models trained on half a billion scraped LinkedIn records.
Upload CSVs or paste text, generate 1024D embeddings (v1–v4), PCA viz, and download results!
Try it: cjerzak/LinkOrgs_Online
Details/paper: https://connorjerzak.com/linkorgs-summary/
Training/inference code: https://github.com/cjerzak/LinkOrgs-software
Upload CSVs or paste text, generate 1024D embeddings (v1–v4), PCA viz, and download results!
Try it: cjerzak/LinkOrgs_Online
Details/paper: https://connorjerzak.com/linkorgs-summary/
Training/inference code: https://github.com/cjerzak/LinkOrgs-software
Post
371
Just dropped IWI-Africa: 69k DHS clusters linked with satellite imagery + agent/LLM text so you can predict wealth from space and the web. Poke the vision-language-agentic convergence yourself.
Hugging Face: theaidevlab/IWI-Africa-Multimodal
Paper: https://arxiv.org/abs/2508.01109.
Hugging Face: theaidevlab/IWI-Africa-Multimodal
Paper: https://arxiv.org/abs/2508.01109.
cjerzak
updated
a
collection
6 months ago
cjerzak
updated
a
dataset
6 months ago
cjerzak
authored
3
papers
6 months ago
Attenuation Bias with Latent Predictors
Paper
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2507.22218
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Published
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1
Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty?
Paper
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2508.01109
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Published
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4
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis
Paper
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2508.01341
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Published
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1
cjerzak
published
a
dataset
6 months ago
Post
266
Global Leadership Project v1 dataset released: 50k+ political elites, 156 countries, hand-coded. v2 in progress.
HF link: cjerzak/GlobalLeadershipProject_v1
HF link: cjerzak/GlobalLeadershipProject_v1
Post
2358
Dropped a dataset on here for linking org data: half a billion records scraped from LinkedIn networks. Positive/negative matches, bipartite graphs, Markov clusters – all the goods to train models that actually work on fuzzy company names.
NegMatches, PosMatches, holdouts for eval.
Check it out: cjerzak/LinkOrgs
NegMatches, PosMatches, holdouts for eval.
Check it out: cjerzak/LinkOrgs
cjerzak
updated
a
collection
7 months ago
cjerzak
updated
a
collection
8 months ago