Research Themes
The LILI Lab develops interpretable machine learning and statistical methods for inverse problems, where key information cannot be measured directly. Our work focuses on spatiotemporal data in medical imaging, disease progression modelling, computer vision, and ecological monitoring.
Explore our four main research themes:
Medical Image Analysis
Work on MRI reconstruction, image registration, and related inverse problems.
Progression Modelling
Probabilistic latent variable modelling of neurodevelopment and degeneration.
Computer Vision
Projects spanning visual recognition, reconstruction, and interpretable models for vision tasks.
Ecological Monitoring
Interpretable learning for ecological data, from species monitoring to environmental sensing.
Machine Learning Methods
Core methodological work on probabilistic modeling, interpretability, and efficient training for inverse problems.