I am a PhD candidate in machine learning theory at EPFL, advised by Nicolas Flammarion in the Theory of Machine Learning Lab. My research develops rigorous theory to explain how pretraining works: what learning systems learn, why they generalize, and how useful structure emerges during training. I am increasingly bringing this perspective to interpretability as a foundation for alignment and control.