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I am an assistant professor for data science in diabetes care at the University of Bern, where I am affiliated with the University of Bern Clinic for Diabetology, Endocrinology, Nutritional Medicine and Metabolism (UDEM) and the Diabetes Center Berne (DCB). My long-term goal is to develop certifiably safe, reliable and effective data science tools for patient-specific treatment systems. I have a background in academic research as well as developing data science products for medical devices, with a strong focus on technology that can ultimately benefit patient health in a safe and trustworthy way.

Bio: After an undergraduate degree in electrical (BSc) and biomedical engineering (MSc) at ETH Zürich, Switzerland, I did a PhD in machine learning for medical image analysis at Imperial College London, UK. After a post-doc at ETH Zürich I joined the Swiss wearable medical device startup Ava, where I eventually became the data science team lead. In this position, I came to appreciate the need for demonstrably safe machine learning in healthcare. In 2021, I returned to academic research to pursue research on this topic as a group leader for machine learning in medical diagnostics in the Berens lab at the Hertie Institute for AI in Brain Health at the University of Tübingen, Germany, where I still hold a part-time appointment.

I’m a postdoctoral researcher in the Machine Learning for Medicine lab. I hold PhD and MSc in computer science from the University of Campinas, Brazil, as well as a BSc in computer engineering from the Federal University of São Carlos, Brazil.

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