Corentin Dancette is a machine learning researcher with 11 years of technical experience, currently building foundation models for radiology at Raidium. He completed a PhD in deep learning at Sorbonne Université, focusing on multimodal vision-and-language problems such as Visual Question Answering, and interned at Meta AI on making VQA models more reliable. Comfortable moving between research and engineering, he has hands-on experience across data engineering, speech representation learning, and production-oriented tooling from internships at Datadog and academic labs. Based in Paris, he blends rigorous academic training with applied ML engineering to translate complex multimodal research into domain-specific foundation models for healthcare. An early background in systems and networks gives him a practical edge when deploying large models in real-world environments.
11 years of coding experience
2 years of employment as a software developer
Engineer’s Degree, Engineering, Engineer’s Degree, Engineering at Ecole Centrale Paris
Master's degree, Computer Science - Artificial Intelligence, 6 months at the Georgia Tech french campus, and 6 months at the Atlanta Campus, Master's degree, Computer Science - Artificial Intelligence, 6 months at the Georgia Tech french campus, and 6 months at the Atlanta Campus at Georgia Institute of Technology
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Corentin Dancette - Machine Learning Researcher at Raidium