I lead the Medical AI Group at the Idiap Research Institute in Martigny, Switzerland, where I work on machine learning and computer vision for medical decision making, with a lasting commitment to research reproducibility and open science.
- Medical AI
- Machine Learning
- Computer Vision
- Signal Processing
- Reproducible Research
Selected projects
Current lines of work — every project, including earlier-career ones, is on the Projects page.
Ophthalmology — Uveitis
AI-assisted grading of intraocular inflammation in uveitis from retinal fluorescein angiography, developed with the Jules-Gonin Eye Hospital.
Neurophysiology — Sleep Medicine
Generalisable, reproducible automatic sleep-stage classification from polysomnography, working toward foundation models for sleep medicine.
Trustworthy and Fair Medical AI
Making medical AI fair across patient subgroups and useful in the clinic, with evaluation frameworks, foundation-model bias analysis, and utility-fairness trade-offs.
Ophthalmology — Retinal Image Analysis
Segmentation and analysis of retinal fundus images (vessels, optic disc, blood flow) with minimalistic, reproducible, and clinically deployable models.
Latest research outputs
The four most recent — the Research Outputs page contains a complete list.
Journal Article
UveAI: clinic-ready scoring of retinal inflammation in uveitis on widefield fluorescein angiography using AI
Journal Article
Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives
Conference Paper
When Specialization Helps (and Hurts): Cross-Modality Transfer in Ophthalmic Imaging with Foundation Models
Journal Article
A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems