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UID:pretalx-scipy-2026-9FQMMN@pretalx.com
DTSTART;TZID=CST:20260713T133000
DTEND;TZID=CST:20260713T173000
DESCRIPTION:Scientific researchers need reproducible software environments 
 for complex applications that can run across heterogeneous computing platf
 orms. Modern open source tools\, like [Pixi](https://pixi.sh/)\, provide a
 utomatic reproducibility solutions for all dependencies while providing a 
 high level interface well suited for researchers.\n\nThis tutorial will pr
 ovide a practical introduction to using Pixi to easily create scientific a
 nd AI/ML environments that benefit from hardware acceleration\, across mul
 tiple machines and platforms. The focus will be on CUDA applications\, suc
 h as machine learning frameworks and use of CUDA Tile\, as well as using p
 ixi-build to construct bespoke CUDA enabled conda packages.\n\nInstallatio
 n Instructions: https://matthewfeickert-talks.github.io/reproducible-cuda-
 workflows-with-pixi-scipy-2026/setup/
DTSTAMP:20260715T021141Z
LOCATION:Accelerated Computing
SUMMARY:Reproducible CUDA Accelerated Workflows for Scientists with Pixi (R
 oom HSEC 2-138) - Matthew Feickert\, Ruben Arts\, Katrina Riehl
URL:https://pretalx.com/scipy-2026/talk/9FQMMN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-scipy-2026-RKS93M@pretalx.com
DTSTART;TZID=CST:20260716T174500
DTEND;TZID=CST:20260716T184000
DESCRIPTION:Supply chain attacks on Python\, including recent compromises o
 f popular packages and CI workflows\, have exposed structural weaknesses i
 n the scientific Python ecosystem. This BoF will bring together library ma
 intainers\, downstream users\, and security practitioners to discuss pract
 ical strategies for securing scientific Python stacks\, from core packages
  (NumPy/SciPy) to domain libraries and analysis workflows. We will share c
 urrent efforts (e.g.\, SPEC 8\, Trusted Publishing\, SBOM generation\, Git
 Hub Actions hardening)\, identify pain points and gaps\, and brainstorm ac
 tionable steps the community can take over the next year to make scientifi
 c Python releases more trustworthy by default. Join us to share your exper
 iences\, challenges\, and ideas on fortifying our open-source projects aga
 inst potential threats and ensuring the integrity of scientific research.
DTSTAMP:20260715T021141Z
LOCATION:Memorial Hall
SUMMARY:Securing the Scientific Python Supply Chain - Juanita Gomez\, Jarro
 d Millman\, Matthew Feickert
URL:https://pretalx.com/scipy-2026/talk/RKS93M/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-scipy-2026-WFXBKQ@pretalx.com
DTSTART;TZID=CST:20260717T174500
DTEND;TZID=CST:20260717T184000
DESCRIPTION:Until very recently\, producing and using reproducible scientif
 ic software environments required advanced knowledge and a strict adherenc
 e to best practices (e.g. DOI: 10.25080/majora-212e5952-028). Now\, with t
 he advent of modern tooling with lockfile-first workflows (i.e. Pixi and u
 v)\, and the emergence of lockfile standards across scientific open source
 \, applications can be made reproducible at the digest level through tooli
 ng decisions. As this technology and practices become increasingly common 
 there is an opportunity to define common best practices around lockfile ba
 sed software development that can further reduce developer overhead and ma
 intenance burden. This Birds of a Feather panel will focus on how experien
 ced developers are leveraging lockfiles across software development\, appl
 ications\, and deployment while providing best practices and practical rec
 ommendations\, while also highlighting continuing challenges and opportuni
 ties for improvement.
DTSTAMP:20260715T021141Z
LOCATION:Johnson Great Room
SUMMARY:Lockfile-based development and applications - Naty Clementi\, Matth
 ew Feickert\, Ruben Arts\, Gil Forsyth\, Henry Schreiner
URL:https://pretalx.com/scipy-2026/talk/WFXBKQ/
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