iiinova — where your digital self keeps evolving

Charlie Rahal @crahal.com · 20/08/2026

How reliable is research 🤔? We publish RobustiPy in @cp-patterns.bsky.social: a highly accessible, #GNU-GPL 3.0 #python lib for #robustness analysis and #datascience. It may represent the “next generation” of #modeluncertainty, bringing a range of frontier #statistics methods into one toolkit 📊📈!

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Charlie Rahal @crahal.com · 19/05/2026

CW: suicide. Honoured to be Guest Editing—with @saurabhkhanna.bsky.social—a Special Issue at ACM-TSC in tribute of my intellectual hero, Aaron Swartz, who died by suicide in 2013 at 26 after extreme prosecutorial overreach. While attempting to expand access to knowledge. CfP: tinyurl.com/4znbk4y2.

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Charlie Rahal @crahal.com · 11/05/2026

Two weeks left until our Call for Papers closes for the 7th International Conference on Social Computing (ICSC'26). Please do submit your papers! Optional conference proceedings, great keynote speakers, nice conference dinner @nuffieldcollege.bsky.social, and more. Details: icsc-conf.github.io!

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Charlie Rahal @crahal.com · 04/05/2026

Today's pushes bring in some speed efficiencies to our new model uncertainty library which make it approximately **14** times faster! Check it out now at robustipy.github.io; accompanying paper getting published very soon, super jazzed 🎷

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Charlie Rahal @crahal.com · 17/07/2025

@ramina-sotoudeh.bsky.social gave an AMAZING talk yesterday as part of the #metrics-and-models seminar series👏. Next (30.07), we have @klint.bsky.social on "Reproducing Expert Judgement with Shortened Surveys using Simulated Annealing"🔥! See website for more; metrics-and-models.github.io!

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Charlie Rahal @crahal.com · 30/06/2025

Hurrying to post about RobustiPy, i forgot this fun animation i made for teaching purposes (with @deevybee.bsky.social on the SABS R3 CDT) around when we started developing. Specification uncertainty is just _one_ type of uncertainty, though; our forthcoming work looks at the role of random numbers!

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Charlie Rahal @crahal.com · 30/06/2025

We also think it has some tight #dataviz, too! Here's the canonical `union.dta' dataset examined by other model uncertainty tools. See our paper and website for more examples of how to use the accessible Python app, released under an open source GNU GPL 3.0 license!

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Charlie Rahal @crahal.com · 31/05/2025

if you can out-do us with the pretention of this, i will salute you: arxiv.org/pdf/2411.19223

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Charlie Rahal @crahal.com · 27/03/2025

1/5 📄✨ITS FINALLY HERE!📄✨. After _five_ years, our new model evaluation metric — The InterModel Vigorish (IMV) — is now published (@plosone.org). Paper: bit.ly/3RlqrQH Preprint: bit.ly/41LzGjm Code: github.com/intermodelvigorish ‘What’s the vig on this action?’ (bit.ly/4hPoZ3Z). ⬇️⬇️⬇️

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Charlie Rahal @crahal.com · 15/03/2025

🎉🚀🔬Our new model uncertainty library -- RobustiPy -- now also has joint inference tests (as per @urisohn.bsky.social et al., 2019, NHB). Near to release/preprint! GitHub: github.com/RobustiPy/robustipy project website: robustipy.github.io/ /w @dvaldenegro.bsky.social & @jiani-y.bsky.social!🎉🚀🔬

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Charlie Rahal @crahal.com · 24/02/2025

In an age when so much modern scientific conversation surrounds 'Artificial General Intelligence', lets not forget that René Descartes -- in De homine (1662) -- claimed that non-human animals could be explained reductively as automata.

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Charlie Rahal @crahal.com · 25/12/2024

“you will be visited by three types of epistemic error” arxiv.org/abs/2411.19223

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Charlie Rahal @crahal.com · 10/12/2024

Now on arXiv! We design a new two-stage Individual Synthetic Control algorithm to cleanly identify causal estimates of the “caring penalty.” High-intensity unpaid carers face ~45% personal losses; households lose ~12%. 🏠📉 Link: arxiv.org/abs/2411.10314 Blog: shorturl.at/IVQ6M

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Charlie Rahal @crahal.com · 25/11/2024

Having spent much of the summer in China talking about LLMs in general, I can absolutely confirm that this is true.

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