Bryce Wang @bryceWCoPaperAI
Founder of StatsPai Building https://t.co/sqYBSThFu1 — AI research co-author https://t.co/I5vYNNyBUE | https://t.co/dd6oOKtevA statspai.com Stanford, CA, US Joined July 2018-
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StatsPAI, Agent-native Causal Inference Open-sourced Library in Python. Built and maintained by Stanford REAP. Repo: github.com/brycewang-stan…
StatsPAI, Agent-native Causal Inference Open-sourced Library in Python youtu.be/29DxNAnukqM?si… via @YouTube @StatsPai @causalinference @econometrics #Stata #Python #R #CausalInference #Regression #Statistics
Move fast. Break thru.
StatsPAI 1.6.0: 250,000 lines of code, 925 functions I originally planned to release version 1.0.0, but ended up writing another 30,000 lines overnight and jumped straight to 1.6. This is simply the pace of the AI era—tools like this are being rapidly brought into existence.
This is exactly the kind of tooling we need. Turning plotting from a manual craft into a reproducible system. StatsPai is quietly building the “Stata → Python” bridge. #Python #Stata #Econometirc #Econ #Economics #ScocialScience
Finally, a Stata Graph Editor clone for matplotlib. 29 themes, auto-generates Python code, one line to use. pip install statspai Open source. Your reproducible workflow just got a lot smoother.
Introducing StatsPAI — an open-source econometrics toolkit for the AI agent era. 150+ functions. One unified API. From OLS to causal forests. pip install statspai github.com/brycewang-stan…
Rebuilding the Python Econometrics Ecosystem in the AI era!🫡
Introducing StatsPAI (Stanford REAP & CoPaper.AI): our vision is to build the unified Python toolkit for causal inference & econometrics. One import, every method: DID, synthetic control, IV, RDD, matching, and more. pip install statspai 💻 github.com/brycewang-stan…
🔬 We open-sourced 23,000+ agent skills for empirical research across 8 social science disciplines. Skills encode full research methodology — so AI agents know what a complete DID/IV/RDD analysis looks like, not just individual steps. github.com/brycewang-stan…
Most researchers spend weeks coding Causal Forest, DML, or Synthetic DID from scratch. CoPaper.AI now supports 6 frontier ML × Causal Inference methods. Pick your method → auto-configure → get executable code + publication-ready paper.
Every empirical paper has the same DNA: P1 Introduction — why it matters P2 Data & Methods — how you test it P3 Results — what you found P4 Conclusion — what it means CoPaper.AI generates all 4 parts from your dataset automatically. Try free. @CoPaper.AI
Check out my latest article: From raw data to a full empirical paper draft — regressions, tables, figures, and structured writing — in one workflow. I built an AI co-pilot that do linkedin.com/pulse/from-raw… via @LinkedIn
🚀 CoPaper.AI: We’re building an AI-powered research & analytics startup and hiring interns across product, full-stack, marketing, UX, stats tooling & ops! 📍 Work directly with the team, grow fast, and accelerate the empirical research. statspai.com/join
CoPaper is the first expression of that idea: an AI research co-author, not a paper writer — designed to support analysis, reasoning, and iteration from data to paper. 🧐💪
Statspai was started to turn those research practices into systems — making empirical analysis and paper-building more structured and reproducible, while keeping researchers firmly in the loop. 😐
After months of building 😆😆, I’m excited to share CoPaper.ai — an AI research co-author that works with you, not instead of you. 😅😅 Built by StatsPai.com, and originating from research and applied work with the Stanford REAP team, CoPaper helps turn data, empirical analysis, and ideas into papers, together. We’re opening a private beta (invite-only). 👉 copaper.ai 🤖🤖 If you’re interested, feel free to DM me. 😀😀
LangSmith Agent Builder: describe the agent you want in plain English, get a Deep Agents worker that reads emails, Slack, calendars—and acts on them automatically. No triggers needed to wait around. New emails or Slack messages wake it up. docs.langchain.com/langsmith/agen…
Here's how Claude Sonnet 4.5 trades off terminal illness sufferers across countries. Nigerians are worth 27 times as much as Germans, and as with GPT-4o there's an Africa > South Asia > other > Europe/US rank-order.
New blog post (link below). This one's not an essay, it's an investigation of how LLMs trade off different lives. In February 2025, the Center for AI Safety published "Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs" in which they showed, among many
Using Skills with the Claude Agent SDK How do you use skills to build agents? Here's an example demo I've built using one of our premade skills to make an excel demo agent.
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