This site is dedicated to make my research, software and publications easily accessible. The majority of my research is set at the intersection between big data, machine learning and medical imaging data with the ultimate goal of improving outcome prediction in various diseases, such as stroke. To do so, I aim to unravel the complex relationships between what we can see on images and the clinical presentation.
Research topics
Medical Image Analysis
The power to investigate disease states and progressions non-invasively.
Machine Learning
The ability to process big data and give clinicians the time to focus on the patient.
Big Data
The resources to find the biomarkers that matter and unveil complex relationships.
Harnessing the potential of clinical images
Bringing advanced analyses techniques to the clinic
Effective reserve
Investigating the brains capacity to compensate for negative effects, such as chronic and/or acute disease.
Connectomics
Utilizing the complex interconnected nature of the brain to understand higher order relationships.
Understanding diseases and outcomes
Uncovering the contributing factors of disease progression with the goal to model and improve the outcome of patients.
Pipeline development
Automation of phenotype characterization with modern analyses techniques in clinical imaging data.