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AIAS+ 2026 : Chen Institute Symposium for AI Advancing Society and Science

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Link: https://www.aiasplus.org/call-for-papers
 
When Nov 5, 2026 - Nov 7, 2026
Where San Francisco, California, USA
Submission Deadline Jul 15, 2026
Notification Due Aug 29, 2026
Final Version Due Sep 7, 2026
Categories    artificial intelligence   research automation   frontier ai methods   scientific reasoning
 

Call For Papers

We invite submissions that explore how core advancements in artificial intelligence are accelerating progress in science. AIAS 2026 focuses on transformative AI innovations that expand the boundaries of scientific discovery, from models that support prediction, interpretation, and simulation to systems that enable reasoning, hypothesis generation, and experimental discovery.

We welcome work across disciplines that advances AI as an increasingly active partner in the scientific process. In particular, we encourage contributions that develop new AI methods, deepen established directions, or demonstrate impactful applications in scientific domains.

Topics of interest include, but are not limited to:

• Foundational and frontier AI methods for scientific discovery
• Scientific reasoning, inference, and decision-making
• Hypothesis generation and discovery-oriented modeling
• AI for simulation, prediction, and interpretation in science
• Research process automation, including literature synthesis, data analysis, and experimental design
• AI systems for biology, chemistry, physics, medicine, engineering, and related fields
• Benchmarks, evaluation methods, and infrastructure for AI-accelerated science
• Reliability, robustness, safety, and human oversight in scientific AI systems

AIAS⁺ 2026 is also interested in emerging directions aligned with the broader vision of ‘Discoverative AI’: AI that contributes not only to analysis and prediction, but also to the generation of new questions, new insights, and new pathways for discovery.

We encourage submissions from researchers working at the intersection of AI and the physical, life, and applied sciences, as well as from researchers advancing the foundations of AI in ways that can accelerate scientific progress.

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