Mathieu Blondel

Mathieu Blondel is a Researcher at Google DeepMind in Paris, France. He obtained his PhD in Machine Learning from Kobe University in 2013. From 2013 to 2019, he worked at NTT's Communication Science Laboratories in Kyoto, Japan.

Research Interests:

• Differentiable programming
• Language models and deep learning
• Loss functions for structured prediction
• Optimization algorithms
• Optimal transport theory
• Polynomial networks
• Machine learning software

Scientific Awards:

• Open-science honorable mention at ECML PKDD 2013

Software Contributions: Mathieu is a core contributor to scikit-learn, a foundational Python library for machine learning. He also maintains open-source projects on differentiable sorting, optimal transport, and Fenchel-Young losses.