- Crystal structure databases and associated software development for reproducible science (OPTIMADE).
- Materials and chemical data management for experiment and theory.
- Materials discovery using first principles simulations and surrogate models.
- High-throughput crystal structure prediction with AIRSS, genetic algorithms and related methods.
- Transition-metal phosphides for beyond-Li battery anodes.
Most of my software work can be found on my GitHub.
optimade-python-toolsis a Python library of tools for implementing and consuming OPTIMADE APIs, which I develop and maintain.
OPTIMADEis the specification repository for OPTIMADE, a common REST API for access to materials databases, which I help to develop and maintain. 
MODNetis a package for materials property prediction focused on small datasets, which I help develop and maintain. 
matadoris a Python package for the aggregation, standardisation and analysis of the results of first-principles computations, with a focus on battery materials .
ilustradois a Python package that implements a highly-customisable, massively-parallel genetic algorithm for ab initio crystal structure prediction.
odbx.scienceis a public OPTIMADE API that hosts the Morris group’s crystal structures.