About Me

I am a PhD student specializing in sequential decision-making and reinforcement learning (RL), with a primary focus on explainability. My research aims to overcome the “black box” nature of deep learning agents, developing methods to make RL models more interpretable and trustworthy. I also explore how (interpretable) RL can be applied in practice, such as using offline RL for domains like healthcare.

In my spare time, I am a passionate chess player and enjoy rock climbing.