- Experiment-driven computational simulation of materials
- Representing databases of materials and molecules in two dimensions
- Looking for stable iron nanoparticles
- Understanding the structure of amorphous carbon and silicon with machine learning atomistic modeling
- Automated X-ray photoelectron spectroscopy (XPS) prediction for carbon-based materials: combining DFT, GW and machine learning