Celebrating the “Sci” in SciPy
This track highlights the fantastic scientific applications that the SciPy community creates with the tools we collectively make. Talk proposals to this track should be stories of how using the Scientific Python ecosystem the speakers were able to overcome challenges, create new collaborations, reduce the time to scientific insight, and share their results in ways not previously possible. Proposals should focus on novel applications and problems, and be of broad interest to the conference, but should not shy away from explaining the scientific nuances that make the story in the proposal exciting.

Machine Learning, Data Science, and Explainable AI
This track aims to bring together the latest advances in Data Science and AI/Machine Learning and their applications in science and industry. This includes the development and application of new open-source tools and techniques, as well as novel discoveries in any field made by applying new and existing tools. The last few years have seen historic moments in Generative AI, with larger and more advanced models becoming available that have found applications in areas such as productivity tools and life sciences. We encourage speakers to go beyond the hype and present impactful and meaningful applications of Generative AI in their areas of expertise. We particularly encourage submissions demonstrating progress towards explainability in these models.

Conference Tracks
- General: This track showcases the development and application of new open-source tools in the SciPy ecosystem. We encourage submissions that don’t fit well into any of the existing domain-specific tracks, as well as those that easily span several domains and would benefit a wider audience.
- Earth, Ocean, Geo, and Atmospheric Science: This track welcomes talks showcasing how Python is applied to understand, model, and solve problems in Earth, Ocean, Geo, Climate, and Atmospheric Science.
- Physics and Astronomy: This track highlights the use of Python in scientific open source tools and applications across experimental and theoretical Physics and Astronomy broadly and all their subdomains.
- Bioinformatics, Computational Biology, and Neuroscience: This track welcomes talks demonstrating how Python is advancing research and problem-solving in Bioinformatics, Computational Biology, and Neuroscience. Submissions can highlight Python libraries or workflows used to analyze data, create models, or simulate systems in these fields.
- Teaching and Learning: This track focuses on experiences, best practices, and tools for teaching, learning, and staying informed about the rapidly evolving field of scientific computing. Key themes include effective assignments, innovative pedagogical approaches, tools that are well-suited for classroom environments, and examples of student engagement with scientific computing. Learning occurs in a range of settings, from formal classrooms to industry contexts to self-directed exploration. We encourage submissions that reflect this diversity, including talks that share experiences with self-teaching or highlight resources for learning new skills outside of a traditional classroom setting.
- Maintainers and Community: This track invites talks that celebrate the work of maintainers and the power of community in the Python ecosystem. Submissions can focus on lessons learned from maintaining open-source projects, updates in libraries used in Scientific Python, or fostering inclusive communities.

The Call for Proposals is Closed.