CHOOSE Forum 2026: Software Engineering, AI & Scientific Computing

The CHOOSE Forum is back! After a break during and following the COVID-19 pandemic, we are now preparing to reestablish the annual forum; though the forum used to be a standalone event, we co-locate its first edition after the break to make the most of the opportunity that  SE2026 is taking place in Switzerland, fostering valuable exchange with the broader software engineering community.

Aims and Scope

The  CHOOSE Forum 2026, co-located with  SE2026, brings together experts from software engineering, artificial intelligence, and scientists from other domains to explore the evolving intersections of these fields. With growing interest in the dependability of AI-based systems and the rigor of scientific research, this event provides a unique platform for open dialogue, shared challenges, and cross-disciplinary collaboration.

As AI becomes more deeply embedded in both industrial and scientific domains - ranging from healthcare and mobility to life sciences and finance - a specific duality emerges: while their goals may differ, both sectors increasingly depend on AI-driven software. This brings not only tremendous research opportunities but also common challenges, such as ensuring robustness, transparency, and scientific rigor. At the same time, the scientific community’s growing emphasis on reproducibility, the value of negative results, and integrated data pipelines highlight the need for principled approaches to software engineering - challenges that closely mirror those in industry.

For details about time and location of the CHOOSE Forum, check the  SE2026 - CHOOSE Forum page.

Format of the Forum

• Academic–Industry Collaboration. The forum welcomes participants from both academia and industry to ensure a dynamic exchange between theoretical advances and applied challenges.
• Expanded Themes Beyond SE & AI. In addition to core topics - such as software verification, testing, and the trustworthiness of AI systems - the event will feature sessions on reproducible research methods, open data/code practices, and the importance of publishing and learning from negative results.
• Cross-Disciplinary Panels and Talks. Panels will include voices from AI, SE, and life sciences, fostering deep discussion on building reliable systems and reproducible scientific computing. Dedicated talks will also cover current challenges in AI, software engineering, and innovations in bioinformatics.
• Case Studies and Practical Insights. Industry and academic partners will present real-world case studies showing how rigorous engineering and AI contribute to more trustworthy software and scientific outcomes.
• Community & Collaboration. Attendees will have rich opportunities to connect across disciplines, sharing tools, ideas, and perspectives to help shape more dependable technologies and reproducible science.

This event is ideal for software engineers, AI researchers, bioinformaticians, life science professionals, and academic scholars seeking to build more reliable, transparent, and collaborative systems and science.

Program

For the detailed program, check the  SE2026 - CHOOSE Forum page.

Organisation

•  Sebastiano Panichella, University of Bern (CH)
•  Andreas Fischer, University of Fribourg (CH)
•  Matteo Biagiola, University of St. Gallen (CH)