Welcome

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I am an associate professor (“maître de conférences” in french) in optimization and machine learning at the mathematical institute of the university of Bordeaux (IMB).

From 2022 to 2024, I was a postdoc at the University of Tübingen, working on the TRINOM-DS project led by Peter Ochs and Jalal Fadili. Prior to that, I wrote my PhD thesis (available here) at the IRIT laboratory in Toulouse (supervised by Cédric Févotte, Edouard Pauwels and Jérôme Bolte). I was a member of the FACTORY project.

My research focuses on optimization algorithms for machine learning (mainly second-order methods with application to deep learning), and learning optimization algorithms.

Research interests

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• Continuous optimization (convex & non-convex, non-smooth, stochastic)
• Learning to optimize
• Optimization for deep learning & automatic hyper-parameter tuning

Selected publications

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From learning to optimize to learning optimization algorithms (2025)

C. Castera, P. Ochs
To appear at AISTATS 2025
arXiv

Continuous Newton-like methods featuring inertia and variable mass (2024)

C. Castera, H. Attouch, J. Fadili, P. Ochs
SIAM Journal on Optimization (SIOPT)
SIOPT | arXiv

An inertial Newton algorithm for deep learning (2021)

C. Castera, J. Bolte, C. Févotte, E. Pauwels
Journal of Machine Learning Research (JMLR)
JMLR | Hal | Code | Poster

Near-optimal closed-loop method via Lyapunov damping for convex optimization (2023)

S. Maier, C. Castera, P. Ochs
Preprint
arXiv | Code

Teaching (University of Bordeaux)

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• Large-scale optimization (Master 2)
• Introduction to deep learning (Master 2)
• Convex optimization (Master 1)
• Image processing (Licence 3)
• Tutoring projects on image processing and machine learning

Contact

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[firstname].[lastname]@math.u-bordeaux.fr