I am currently working on topics related to machine learning for medical imaging (e.g., robustness, building foundational models, generative models, software engineering, etc.)

During my Phd I worked at the intersection of machine learning and software engineering, looking for ways to design, develop and maintain robust machine learning solutions. Since robustness has broad implications along each stage of the development life cycle, I studied robustness both from a system (engineering) and from an algorithmic prescriptive.

Some quick pointers to our work are the Software Engineering for Machine Learning website, where we study the system perspective and connect it to global frameworks such the EU Ethics Guidelines for Trustworthy AI or our publications on algorithmic robustness for computer vision and planning.