Most of my programming is related to my research in computational materials science. I believe that strong computational science benefits from strong software engineering, and that all scientific academic software should be open source.
I am involved in the following software projects.
- PyBerny—Python package for optimizing molecular geometries, supported by PySCF, ASE, and QCEngine
- Libmbd—Fortran/Python library implementing the many-body dispersion method, embedded in FHI-aims and DFTB+
- DeepQMC—Pytorch implementation of quantum Monte Carlo with deep neural network ansatzes
These are experimental packages that, although fully functional, I don’t yet consider finished.
- KnitJ—alternative front-end to Jupyter kernels aiming at editor freedom and easy versioning
- Mona—framework for reproducible and distributed, potentially long-running calculations
- FHI-aims—massively parallel electronic structure code package with DFT at its core