Emerging Algorithms and Mathematical Paradigms for Reliable Next-Generation AI
A workshop advancing foundational mathematics and algorithms for reliable, robust, and interpretable next-generation AI, emphasizing interdisciplinary collaboration between academia and industry.
Funder: Institute for Pure and Applied Mathematics
Due Dates: December 7, 2026 (application submission deadline; fullest consideration)
Funding Amounts: Travel support available, especially for early-career researchers; registration fees: $10–$100 depending on category
Summary: Workshop supporting the development of foundational algorithms and mathematics to ensure reliable, safe, and robust next-generation AI, fostering academia-industry collaboration.
Key Information: All applicants (including those not requesting funding) must apply and be invited; limited seating.
Description
This workshop brings together leading researchers from mathematics, computer science, and industry to advance new algorithms and mathematical paradigms for reliable, accurate, and safe next-generation artificial intelligence. Focus areas include the foundational role of sampling in AI (Bayesian inference, scientific simulation, uncertainty quantification), robust and interpretable AI, and bridging theoretical mathematics with computational practice. The event emphasizes interdisciplinary collaboration and aims to address the challenges of large-scale, probabilistic AI systems by fostering dialogue between academia and industry.
