Teaching
Teaching Activities
Master MIA
Practical Work: Introduction to Deep Learning, Faculté des Sciences d'Orsay - Université Paris Saclay, 2025
Tutorial 1: Introduction to Pytorch
Tutorial Correction
Tutorial 2: Hyperparameters and Architecture Optimization
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Tutorial 3: Convolutional Neural Networks (CNNs)
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Tutorial 4: Generative Models (GANs)
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Tutorial 5: Generative Models (Diffusion)
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Tutorial 6: Recurrent Neural Networks (RNNs)
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Tutorial 7: Graph Neural Networks
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Internship Supervision
2026 — INRIA Paris
Haidar Ali Yousef, Statistical climate downscaling with generative models
February 2026 – July 2026
Co-supervised with Anastase Charantonis.Elyas Chikhaoui, Symbolic regression for satellite data using DRAGON
January 2026 – June 2026
Co-supervised with Anastase Charantonis.
2024 — EDF R&D
Keshav Das, Automated selection of adaptive additive models, application to load consumption forecasting
September 2024 – February 2025
Co-supervised with Margaux Brégère and Amaury Durand.Alban Derepas, Future evolution of the wind resource and the interest of machine learning methods for statistical wind downscaling
May 2024 – November 2024
Co-supervised with Boutheina Oueslati, Yannig Goude, and Claire Monteleoni.Roxane Goffinet, Global forecasting models for a large number of time series
March 2024 – October 2024
Co-supervised with Bachir Hamrouche and Guillaume Lambert.