I'm an applied physics student at EPFL, currently working on my master's thesis on the heat capacity of MOF-5 using machine-learning interatomic potentials and sparse automatic differentiation for efficient computation.
I enjoy developing scalable, readable, well-documented, and well-tested APIs and libraries in Python and C/C++. I am also interested in contributing to open-source projects in computational physics, machine learning, and software engineering.
- Python and C/C++ APIs, libraries, documentation, tests
- Machine learning, computer vision, NLP, and data science
- Scientific computing and physics simulations
- Graphics programming and mathematical visualization
- Basic frontend development with React
