"Streamlining nature’s blueprint: Calculating the quantum dance of eigenstates and eigenvalues on autopilot"

I specialise in Density Functional Theory (DFT) and Machine Learning Interatomic Potentials (MLIPs), working at the intersection of quantum chemistry and artificial intelligence to solve complex materials science problems.

Current Focus 🎯

• Investigating the role of the "attention" mechanism in interpreting our physical reality.

Technical Arsenal 🛠️

• Quantum Chemistry: Electronic structure theory, Solid State Chemistry
• Computational Tools: pymatgen, ASE, VASP, Quantum ESPRESSO, Gaussian, MACE

I believe in the power of computational science to unlock nature's secrets, where every eigenstate tells a story, and every eigenvalue holds a key to understanding our world at the atomic level.

Adaptable by nature, driven by curiosity, powered by quantum mechanics.