I am interested in the environmental impact of computer-based research. We developed the Green Algorithms project to push forward the discussion around this issue. More info here and on www.green-algorithms.org

I’m also interested in radiogenomics in cardiovascular diseases: how can we leverage modern imaging data (such as cardiac MRI), machine learning models and genetic information to better understand cardiovascular diseases.

During my PhD, I focused on better understanding and standardising the prediction of Protein-Protein Interactions (PPIs) using Machine Learning. More

I also contribute to clinical studies to advise on statistical methodology.

Selected publications

A complete list of publications is available on the “publications” tab and on Google Scholar.

Selected talks (for an overview of the Green Algorithms projects)

A full list of talks with links to slides and recordings (when available) can be found here.

For (computational) biologists:
The environmental impact of computational biology
EMBL-EBI's training webinar, November 2022
[recording and slides]


For data scientists:
The carbon footprint of machine learning: how bad is it and what can we do about it?
Invited talk, SGAI-2022 International Conference on AI (Cambridge, UK), December 2022
[slides]


For trainers:
Training the next generation of sustainable computational scientists
Keynote talk at the "Education in Biology" track at ISMB 2022 (Madison, WI, USA), July 2022
[slides]

Science communication