About myself

I am a PhD student at the Technical University of Denmark at the Department of Applied Mathematics and Computer Science. 

The goal of my project is to explore how various architectural choices and training algorithms affect generalisation in neural networks. By understanding these relationships, I aim to develop strategies that can make the training process more efficient, allowing for faster convergence and improved model accuracy. To achieve this, I draw upon concepts from several branches of pure mathematics, with a particular focus on geometry and algebra. 

I'm passionate about the environment and inclusivity. In my role as a PhD student, I'm eager to contribute to efforts that make academia more sustainable and more welcoming to everyone.

Below you can find my CV (the very long version).