My principal research area lies at the intersection of computer vision, medical image analysis, and machine learning. I specialize in self-supervised learning, test-time adaptation techniques, and multimodal foundation models, aiming to create robust AI systems capable of adapting to changing environments and data distributions, enhancing decision-making in dynamic settings. My work ultimately strives to bridge the gap between cutting-edge machine learning techniques and their ethical and impactful deployment in real-world applications.

I'm a senior scientist and lecturer at the Signal Processing Lab (LTS5) at the école Polytechnique Fédérale de Lausanne (EPFL), with a joint affiliation with the Department of Radiology at the Lausanne University Hospital (CHUV) in Lausanne, Switzerland. At the EPFL-LTS5, I am the computer vision team leader for the medical imaging group. I am a member of the European Lab for Learning & Intelligent Systems (ELLIS) and contribute to EPFL's ELLIS Unit.
I lead a dynamic team of Ph.D. and Master's students, developing state-of-the-art methodologies in computer vision, machine learning, and medical image analysis. I have authored peer-reviewed publications in top-tier conferences and journals, including ICLR, CVPR, and ICCV. My leadership roles include serving as an Area Chair for CVPR and as a member of the editorial boards for several prominent computer vision journals. I have a proven track record in securing competitive research funding from organizations such as the PHRT and the Swiss Cancer League. Additionally, I successfully led large-scale initiatives, such as serving as the EPFL team leader for the European Horizon 2020 project ADAS&ME, showcasing my ability to manage complex, multidisciplinary collaborations focused on safe and responsible AI applications.