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.

Research interests

My research focuses on several aspects of machine learning for medical data analysis, including:

• Performance generalisation and performance prediction
• Interpretable ML
• Domain shift detection
• Uncertainty quantification
• Neural network calibration

Open positions

Contact me if you are interested in a PhD position or a MSc thesis project

Teaching

• Lecture: Machine Learning I (Winter semester 2023/2024)
• Seminar: Machine Learning for Medical Image Analysis (Winter semester 2022/2023)
• Seminar: Machine Learning for Medical Image Analysis (Winter semester 2021/2022)

News

• April 2024: I started as an assistant professor at the University of Bern, Switzerland.
• February 2023: We had two papers accepted at MIDL 2023.
• December 2022: I was an invited speaker at the ART 2022 - Advanced Retinal Therapy conference in Vienna, Austria, and presented our work on trustworthy AI in ophthalmology.
• September 2022: I gave an invited talk titled “Towards Safe and Effective Medical Image Analysis Systems” at the ARTORG center in Bern, Switzerland (hybrid), on 18 October.
• July 2022: We are presenting a full and a short paper at MIDL 2022 - come talk to us!
• February 2022: I’m offering a PhD position on performance verification for the safe application of ML systems in medical imaging. Check out jobrxiv for more details, and get in touch if you have any questions!
• December 2021: I was awarded the Athene Grant by the University of Tübingen
• November 2021: The Carl Zeiss Foundation is funding our project “Certification and Foundations of Safe Machine Learning Systems in Healthcare”, led by principal PI Prof. Matthias Hein. Very proud to be part of this excellent group of researchers, and looking forward to the research coming up.
• September 2021: I am teaching the seminar Machine Learning for Medical Image Analysis in the upcoming semester. Sign up now and join us!
• March 2021: I’m looking for motivated students for MSc thesis projects. Please get in touch to find out about potential topics.
• March 2021: I joined the Berens Lab as a group leader for machine learning in medical diagnostics after a few years of industry experience.