With a background in Computer Science and over six years of professional software engineering experience, I am currently bridging the gap between production-level coding standards and complex many-body physics. My research focuses on accelerating the discovery of magnetic materials through Geometric Deep Learning and first-principles data.
- 🔭 Current Research: Developing DSpinGNN, a custom Equivariant Graph Neural Network built from scratch in PyTorch/e3nn, designed to simulate spin-lattice dynamics and magnetization coupling in 2D materials (CrI3).
- ⚙️ Scientific Tooling: Independently developed Phystrackx, a proprietary video-tracking software designed to streamline data acquisition in experimental physics labs.
- 🔬 The Goal: Translating physical symmetries into highly efficient, scalable code to push the boundaries of statistical mechanics and thermal property predictions.
- 🌱 Beyond the Screen: I spend my downtime listening to audiobooks, exploring strategic philosophy, and going on long, calm drives.
| Machine Learning & AI4Science | Physics & HPC | Software Engineering |
   
|
   
|
  
|