I am a postdoctoral researcher fellow at McGill University and Mila (Quebec AI Institute), in collaboration with Prof. David Rolnick and Prof. Etienne Laliberté. My research projects are focused on multi-modal and multi-task deep learning for remote sensing applied to forest monitoring. I am co-founder and chief technical officer (CTO) of Rubisco AI, a Mila startup that aims to monitor forest restoration projects. I was also a core team member of Climate Change AI where I lead the webinar team, co-led the organization of the CCAI workshop at ICLR 2024 and co-organized the CCAI workshop at NeurIPS 2024.

I hold the IVADO Postdoc Entrepreneur Fellowship, which supports my innovative work in forest monitoring. My expertise spans deep learning, computer vision, and remote sensing, with a strong emphasis on sustainability and environmental impact.

I completed my Ph.D. in March 2022 in collaboration between Institut Polytechnique de Paris (Télécom Paris; IDS department, IMAGES Team) and valeo.ai, under the supervision of Patrick Pérez, Florence Tupin and Alasdair Newson. The aim of my Ph.D. work was to use and adapt deep neural network architectures for scene understanding using automotive radar data and multi-sensor fusion. During my Ph.D., I co-organized the Deep Learning Working Group of the IMAGES Team (Télécom Paris). I graduated from M.Sc. Machine Learning and Big Data at Télécom Paris in 2018, M.Sc. (1 and 2) in Statistical Modelling at Paris Panthéon Sorbonne University in 2016 and B.S. in Applied Mathematics at Paris Diderot University in 2014.