Many-body physics leveraging the tools of machine learning.
NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and machine learning techniques.
I helped implement graph-based hamiltonians and an interface with PySCF. For the release of version 2.0 I helped port the C++ to hybrid C++/Python and set up the testing suite using pytest. In addition to helping with documentation and other less technical tasks I set up a binderhub so that users could try/test out NetKet from the web.