DANGER: Data, Numbers, and Geometry (26w5525)
Organizers
Edward Hirst (Queen Mary, University of London)
Miranda Cheng (Academia Sinica, Taiwan)
Sergei Gukov (Caltech)
Elli Heyes (Imperial College London)
Description
The Banff International Research Station will host the "DANGER: Data, Numbers, and Geometry" workshop in Banff from April 5 - 1-, 2026.
As AI continues to revolutionise research in the physical sciences, social sciences, and computer science, there is one field yet to harvest this shed-load of techniques for research: mathematics. As a field routed in analytic precision, application of statistical methods from AI and data science is subtle. However, where mathematical objects number far beyond the scope of human comprehension, and often infinitely, these computational methods are invaluable for processing of this mathematical data and spotting useful patterns too complex to see by eye.
DANGER is a conference at the forefront of data science for mathematics, bringing together leading academics in mathematics to discuss and share how AI methods can accelerate their research, and be used to uncover new connections and conjectures. With a focus on number theory and geometry, datasets like sequences of numbers, or lists of shapes can be quickly generated in bulk and fed into these advanced algorithms for analysis. DANGER aims to foster new collaborations across mathematical fields connected by data science, and motivate the responsible use of AI in research to advance the field.
for Mathematical Innovation and Discovery (BIRS) is a collaborative
Canada-US-Mexico venture that provides an environment for creative
interaction as well as the exchange of ideas, knowledge, and methods
within the Mathematical Sciences, with related disciplines and with
industry. The research station is located at The Banff Centre in
Alberta and is supported by Canada's Natural Science and Engineering
Research Council (NSERC), the U.S. National Science Foundation (NSF),
and Alberta's Advanced Education and Technology.
