Community meetings via Zoom
Our code4math Convenings are regular opportunities for the community to connect via Zoom. Typical Convenings feature a guest speaker whose work promotes or uses the sociotechnical infrastructure of mathematics research.
Follow us on Research Seminars as well!
My hobby: helping mathematicians get up and running with Git/GitHub workflows so they can engage with open-source mathematical software and educational resource projects. And with the advent of GitHub Codespaces, there's no installation required: by just logging into GitHub.com with your free account, you can access all the necessary tools to contribute to a mathematics project using just your web browser! In this talk, I will demo several of my favorite GitHub Codespaces-ready mathematical projects: PreTeXt, pi-Base, LMFDB, Manim, Doenet, and Lean/mathlib. If you'd like to learn more, please check out my handbook [GitHub for Mathematicians](https://g4m.code4math.org/g4m.html), or join us for my [Getting Started with GitHub](https://scholarlattice.org/collections/82bace2a-c3ce-4dfc-9089-4feb05dd8af7) two-day virtual workshop!
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In this talk I will discuss my experiences posting mathematics on social media, and why, how, and what do I post. In particular, I will talk about how mathematics researchers can use technology to improve public perception of mathematics and, in particular, how one can use social media platforms, such as Instagram, TikTok or YouTube, to move the needle and create engaging mathematical content that has a math-positive spin to counter the prevalent math phobia in our society.
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Would your students benefit from an easy-to-use, open-source, web-based word processor that could check their assigned mathematical proofs in real time? In this talk we introduce Lurch Plus, our software project designed specifically for this purpose. We will explain how you can use this software and accompanying course materials, and customize it for your own purposes. While existing proof verification tools like Lean and Isabelle are powerful and effective, they often have steep additional learning curves and can be difficult to customize. We will explain how the custom Lurch validation algorithm overcomes these challenges, and pose some questions for future work.
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