DANGER: Data, Numbers, and Geometry

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.