Julia Dispatch is a podcast about all that matters about Julia. We'll meet the wonderful people who contribute to the community and the language ecosystem. Hear their stories, learn what brought them to Julia, what excites them and how you could potentially follow in their footsteps.
Julia Dispatch
Claim This Podcastby Chris Rackauckas, Michael Tiemann
21 episodes
Updated Daily
Accepts GuestsHas SponsorsLocation 🇺🇸
46
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality62
Social0
YouTube76
Engagement0
Podcast Overview
Julia Dispatch is a podcast about all that matters about Julia. We'll meet the wonderful people who contribute to the community and the language ecosystem. Hear their stories, learn what brought them to Julia, what excites them and how you could potentially follow in their footsteps.
Language
🇺🇲
Publishing Since
10/16/2024
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46
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality62
Social0
YouTube76
Engagement0
8
Excellent Areas
0
Good Performance
11
Growth Opportunities
excellent
Episode Length
1h 13m
Performing excellently!
needs improvement
Publishing Consistency
Every 19 days
Recommendations available
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Recent Episodes
June 12, 2026
Compilers, MLIR, and Hardware Acceleration: The Origin Story of Reactant.jl
<p>In this episode of the Julia Dispatch, hosts Christopher Rackauckas and Michael Tiemann dive into the world of machine learning and compiler engineering with core developers Billy Moses and Avik Pal.We pull back the curtain on the future of high-performance computing in Julia, tracking the evolution of revolutionary compiler tools like Enzyme.jl and Polygeist into their latest groundbreaking collaboration: Reactant.jl. Billy shares how his journey from writing quick-and-dirty Python-to-Java source rewriters in high school eventually led to a PhD at the MIT Julia Lab and a professorship at UIUC. Avik recounts how his background in Google Summer of Code and scientific machine learning (SciML) exposed the structural fragility of language-level neural network optimization—and how Reactant stepped in to solve it.The group explores how Reactant breaks the traditional boundaries of Domain-Specific Languages (DSLs) to automatically optimize generic, loop-heavy, and mutating Julia code directly into MLIR subgraphs, paving the way for next-generation hardware acceleration.Hosts: Chris Rackauckas & Michael TiemannEditor: StaziOfficial Website: https://juliadispatch.fmGitHub Repository: https://github.com/JuliaDispatch/YouTube: https://www.youtube.com/@JuliaDispatchListen via RSS: https://anchor.fm/s/fc63539c/podcast/rss#JuliaLang #MachineLearning #Compilers #SciML #Reactant #Enzyme #OpenSource #TechPodcast</p>
January 1, 2026
Computational Quantum Chemistry with Leticia Madureira
<p>Happy New Year! In this episode, we welcome back Leticia Madureira, a PhD student at Carnegie Mellon University, to explore her journey into quantum chemistry, her passion for Julia, and her work in computational chemistry. Leticia shares her experiences as a PhD student, her contributions to the Julia ecosystem, and her vision for the future of quantum chemistry simulations.</p><p><br></p><p>Leticia Madureira is a PhD candidate in Chemistry at Carnegie Mellon University, specializing in computational quantum chemistry. Her work focuses on electronic structure methods to study chemical processes like polymerization and photodegradation. She collaborates with the Julia Lab to develop open-source, high-performance tools for quantum chemistry, including packages like BasisSets.jl and OohataHuzinaga.jl (under the HartreeFoca organization).Leticia aims to make computational chemistry accessible through teaching and open-source development, believing that education empowers scientists and fosters innovation in the field.</p><p><br></p><p>Recorded on: 2025/10/10</p><p>Hosts: Chris Rackauckas, Michael Tiemann</p><p>Editor: Stazi</p><p><br></p><p>Find us everywhere:</p><p>https://juliadispatch.fm</p><p>https://github.com/JuliaDispatch/</p><p>https://www.youtube.com/@JuliaDispatch</p><p>https://anchor.fm/s/fc63539c/podcast/rss</p>
December 25, 2025
Makie ecosystem with Simon Danisch and Julius Krumbiegel
<p>Merry Chrismas to all who observe! Today, we dive into the world of Makie.jl with its core developers, Simon Danisch and Julius Krumbiegel. We explore the origins of Makie, its unique design philosophy, and its role in shaping the future of visualization in Julia. Simon and Julius share their journeys into Julia, the challenges of building a flexible and performant visualization framework, and their vision for Makie’s future—including ray tracing, higher-level APIs, and integration with the broader Julia ecosystem.</p><p><br></p><p>Simon Danisch began his studies in Cognitive Science at the University of Osnabrück in 2010, specializing in computer vision and machine learning. In 2012, he discovered Julia as a language that combined high performance for interactive computing, seamless GPU integration, and an elegant alternative to object-oriented programming for mathematical applications. Julia has been his primary language ever since. While working with C++ on machine learning projects in 2011, Simon identified a need for interactive, user-friendly tools for data visualization and model parameter manipulation. This inspired his Bachelor’s thesis, where he developed an early predecessor to Makie.jl—some of which remains in use today. Since then, he has made significant contributions to Julia’s graphics, GPU, and plotting infrastructure, and is the author of numerous related packages.</p><p><br></p><p>Julius Krumbiegel joined the Makie project in 2019, where he developed its layout system (GridLayoutBase.jl) and many of the GUI objects originally part of the standalone MakieLayout.jl package. With a background in psychology and vision science, his work focuses on 2D plots, visual quality, and usability, including Makie’s default themes, plot recipes, text and figure layouting, and vector graphics output via CairoMakie.jl. He is also the author of several widely used Julia packages, including Chain.jl, DataFrameMacros.jl, ReadableRegex.jl, Animations.jl, and SankeyMakie.jl.</p><p><br></p><p>Makie's website: https://makie.org/website/</p><p><br></p><p>Recorded on: 2025/11/25</p><p>Hosts: Chris Rackauckas, Michael Tiemann</p><p>Editor: Stazi</p><p><br></p><p>Find us everywhere:</p><p>https://juliadispatch.fm</p><p>https://github.com/JuliaDispatch/</p><p>https://www.youtube.com/@JuliaDispatch</p><p>https://anchor.fm/s/fc63539c/podcast/rss</p>
21 total episodes available
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Frequently asked questions
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- What is Julia Dispatch?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
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