day3

Universes are Big Data: from geometry, to physics, to ML

We briefly overview how historically string theory led theoretical physics first to algebraic/differential geometry, and then to computational geometry, and now to data science.

A Triangle of Influence: Bringing Together Physics, Pure Mathematics, and Computer Science

Recent advances in machine learning have begun creating new bridges to physics and mathematics that have traditionally existed between the latter two. Given this progress, I will speculate about where we are and where things might be headed, including through the recently launched NSF AI Institute for Artificial Intelligence and Fundamental Interactions.

Machine Learning as a Discovery Tool

In this talk, we motivate string theory as a candidate theory of quantum gravity.

Baryons from Mesons: A Machine Learning Perspective

Quantum chromodynamics (QCD) is the theory of the strong interaction. The fundamental particles of QCD, quarks and gluons, carry colour charge and form colourless bound states at low energies.