On April 15, 2022, the CMSA will hold a one-day workshop, Machine Learning and Mathematical Conjecture, related to the New Technologies in Mathematics Seminar Series.

Location: Room G10, 20 Garden Street, Cambridge, MA 02138.

Organizers: Michael R. Douglas (CMSA/Stony Brook/IAIFI) and Peter Chin (CMSA/BU).

Machine learning has driven many exciting recent scientific advances. It has enabled progress on long-standing challenges such as protein folding, and it has helped mathematicians and mathematical physicists create new conjectures and theorems in knot theory, algebraic geometry, and representation theory.

At this workshop, we will bring together mathematicians, theoretical physicists, and machine learning researchers to review the state of the art in machine learning, discuss how ML results can be used to inspire, test and refine precise conjectures, and identify mathematical questions which may be suitable for this approach.

Speakers:

• James Halverson, Northeastern University Dept. of Physics and IAIFI
• Fabian Ruehle, Northeastern University Dept. of Physics and Mathematics and IAIFI
• Andrew Sutherland, MIT Department of Mathematics