AI Fundamentals is HAICON’s home for the core of AI research: new methods and principles, rather than their application to scientific problems. It brings together work on foundation models, generative and multimodal AI, reasoning, agents, representation learning, and trustworthy machine learning.

The track is open to AI/ML researchers at all career stages, from PhD students to senior scientists, in academia and industry, who are developing the next generation of AI methods. Invited keynotes, contributed talks, and posters, selected for scientific novelty and quality, showcase original methodological contributions that advance the foundations of the field.

Participants gain new research ideas, an overview of cutting-edge developments, and opportunities for scientific collaboration, with the AI Applications track building on these foundations in scientific domains.

AI Applications is HAICON’s stage for AI in action: how AI is transforming research across various scientific domains, from climate modeling and drug discovery to materials design, medical imaging, and new tools and workflows. It brings together work on applying and adapting AI methods to real scientific questions and data.

The track is open to researchers at all career stages, from PhD students to senior scientists, in academia and industry, who use AI to advance discovery in their own domains. Invited keynotes, contributed talks, and posters showcase concrete results, practical lessons learned, and tools and workflows that others can adopt in their own research.

Participants gain inspiration for their own work, practical know-how, and connections across disciplines, with the AI Fundamentals track providing the methodological foundations behind these advances.