Here are a few projects that I've worked on recently,
It took over three decades for physicists to recognize that topological defects are responsible for the superfluid helium transition, but what if there was another way to detect these objects with machine learning?
Image super-resolution with neural networks applied to the Ising model. The paper connects concepts from the renormalization group and machine learning.
Qucumber is an python library for performing quantum state tomography with neural networks, in particular, using restricted Boltzmann machine.
Calculating entanglement entropy in conformal field theories and gravity duals, with connections to kinetmatic de Sitter space.