Postdoctoral fellow in computing science. I develop adaptive, individualized interventions for lifelong learning using machine learning and longitudinal data.
I am a postdoctoral fellow at the Department of Computing Science, working within the research initiative Learning and Brain Plasticity throughout the Lifespan. My research applies machine learning and statistical modeling to longitudinal cohort and intervention data in order to predict which individuals benefit from which interventions, with the aim of developing dynamic, adaptive models that can inform future individualized interventions for healthy aging and lifelong learning.
I received my PhD from Université Paris Cité, with a thesis on interpretable machine learning models for high-dimensional behavioral data. My research interests include predictive modeling, privacy-preserving machine learning, federated learning, interpretability, and responsible AI and AI governance. I have previously worked on data governance and AI readiness in international settings, including with UNESCO and UNICEF Innocenti.
The work is carried out in close collaboration with the Department of Statistics and Umeå Center for Functional Brain Imaging (UFBI).