Ruben Arts
Ruben is part of the Prefix.dev core team, builing Pixi and other tools in the package management space. Originally he's a Robotics engineer working on industrial robots, but quickly figuring out that solving development and deployment problems were one of the bigger issues that robotics developers had to deal with. Joining Prefix.dev allowed him to focus on improving the UX/DX of a large group of software engineers. Over the years he's been doing multiple talks and workshops on how to properly manage software and development workflows.
Sessions
Scientific researchers need reproducible software environments for complex applications that can run across heterogeneous computing platforms. Modern open source tools, like Pixi, provide automatic reproducibility solutions for all dependencies while providing a high level interface well suited for researchers.
This tutorial will provide a practical introduction to using Pixi to easily create scientific and AI/ML environments that benefit from hardware acceleration, across multiple machines and platforms. The focus will be on CUDA applications, such as machine learning frameworks and use of CUDA Tile, as well as using pixi-build to construct bespoke CUDA enabled conda packages.
Installation Instructions: https://matthewfeickert-talks.github.io/reproducible-cuda-workflows-with-pixi-scipy-2026/setup/
After 3 years, Pixi is widely adopted in the scientific Python ecosystem. At SciPy 2026, we want to show why.
Scientific Python has specific challenges that Pixi can solve well; a lot of our beloved packages contain C, C++, Rust, CUDA or even Fortran code. With Pixi, a single tool can install the compilers, different Python versions and other build tools in one go, thanks to piggy backing on the years of development that the Conda ecosystem has seen.
Thanks to Pixi’s task system and native multi-platform capabilities, the contributor experience is also enhanced. Daunting tasks like running CMake, installing the correct Rust version or C++ compilers are all hidden away behind a magical: pixi run foobar.
Are you interested to see how you could improve your own workflow and learn from what these big open-source projects are doing? Then you should join this talk! You'll be amazed by what is possible these days.
Until very recently, producing and using reproducible scientific software environments required advanced knowledge and a strict adherence to best practices (e.g. DOI: 10.25080/majora-212e5952-028). Now, with the advent of modern tooling with lockfile-first workflows (i.e. Pixi and uv), and the emergence of lockfile standards across scientific open source, applications can be made reproducible at the digest level through tooling decisions. As this technology and practices become increasingly common there is an opportunity to define common best practices around lockfile based software development that can further reduce developer overhead and maintenance burden. This Birds of a Feather panel will focus on how experienced developers are leveraging lockfiles across software development, applications, and deployment while providing best practices and practical recommendations, while also highlighting continuing challenges and opportunities for improvement.