Irene Balelli
About Irene Balelli
Irene Balelli is a chercheuse specializing in Bayesian learning methods in a federated setting, particularly for health applications. She has held various research positions in France and has contributed to significant projects related to immune response modeling and vaccination strategies against the Ebola virus.
Work at Inria
Irene Balelli has been working at Inria as a chercheuse since 2021. Her role involves the development of Bayesian learning methods in a federated setting, particularly focusing on health applications. She is part of the EPIONE team, which is dedicated to advancing research in this area. Prior to her current position, she served as a chercheur postdoctoral at Inria from 2020 to 2021 in Nice - Sophia Antipolis.
Education and Expertise
Irene Balelli has a strong educational background in mathematics. She studied at Universidad Complutense de Madrid, where she achieved an M1 in Mathematics from 2010 to 2011. She then obtained a Master's degree in Mathématiques appliquées from Université Pierre et Marie Curie (Paris VI) from 2011 to 2013. Her doctoral research, conducted at Université Paris 13 Nord from 2013 to 2016, focused on interactions between mutation, division, and selection mechanisms using probabilistic tools and numerical simulations.
Background
Irene Balelli's professional journey includes significant roles at various institutions. She worked at Inserm as a postdoctoral researcher from 2017 to 2019 in Région de Bordeaux, France. Prior to that, she served as a stagiaire at Université Paris 13 Nord for eight months in 2013. Her academic training also includes a Licentiate degree in Mathematics from Università di Bologna, obtained from 2007 to 2010.
Achievements
During her Ph.D. project, Irene Balelli developed a mathematical framework based on graphs to model antibody affinity maturation of B-cells. This project was part of the Labex Inflamex initiative. Additionally, she contributed to the EBOVAC1 and EBOVAC2 European consortia, which focused on mechanistic modeling of the immune response to a prime-boost vaccination strategy against the Ebola virus.