Summary
Arthur Ouaknine is a postdoctoral researcher and AI practitioner with nine years of experience applying multimodal and multitask deep learning to real-world problems, currently based at McGill University and Mila and supervised by David Rolnick. His work bridges academic rigor and applied impact—spanning automotive radar scene understanding from his PhD (publications at CVPR/ICCV) to developing foundation models for global forest monitoring and co-founding an AI startup for transparent, scalable forest conservation tools. He combines deep expertise in sensor fusion, semantic segmentation and remote sensing with a track record of organizing community knowledge (core team member of Climate Change AI, leading webinars and major workshops). Comfortable moving between research, product and outreach, Arthur brings a rare mix of hands-on model-building, publication pedigree, and entrepreneurial drive focused on climate-relevant AI.
10 years of coding experience
3 years of employment as a software developer
Post M.Sc. Degree Big Data and Machine Learning, Post M.Sc. Degree Big Data and Machine Learning at Télécom Paris
Doctor of Philosophy - PhD Deep Learning, Doctor of Philosophy - PhD Deep Learning at Institut Polytechnique de Paris
Master of Science (M.Sc.) 2 Statistical and Economic Modeling, Master of Science (M.Sc.) 2 Statistical and Economic Modeling at University of Paris I: Panthéon-Sorbonne
Bachelor's degree Applied Mathematics, Bachelor's degree Applied Mathematics at Université Paris Cité
French, English