🎓 PhD Researcher in Machine Learning for Materials Discovery · Imperial College London
💡 Passionate about open, reproducible science and the development of machine-learning models that accelerate materials discovery
My research interests include:
- 🧩 Generative models for inorganic solids
- ⚛️ Geometric graph neural networks
- 🔋 Quantitative evaluation of generative models
- 📊 Open and reproducible software for atomistic machine learning
Machine Learning: PyTorch · Lightning · PyTorch Geometric · scikit-learn
Atomistic Modelling: ASE · MACE · Pymatgen · Materials Project API
Automation & HPC: Snakemake · Hydra · SLURM · W&B
Software Engineering: Git · GitHub Actions · pytest · Docker · Poetry
Reproducibility: Zenodo · Sphinx · Jupyter
Outside research, I enjoy science communication and collaborative software projects that bring transparency to data-driven materials design
🤝 Open to collaborations on generative modelling, dataset curation, and reproducibility in materials informatics