Teaching & Supervision
Supervision
PhDs
I am thrilled to be co-supervising the PhD these of:
- Nina Drobac with Joseph de Vilmarest and Olivier Wintenberger - Online signatures for multivariate time series forecasting
Congratulations to Bianca Marin Moreno, whom I supervised alongside Nadia Oudjane and Pierre Gaillard: she defended her thesis Online convex reinforcement learning and applications to energy management problems on 22 October 2025 and won the “Prix Jeunes Talents France L’Oréal-UNESCO Pour Les Femmes et la Science”!
A big well done to my former student Julie Keisler who defended her thesis Automated Deep Learning: algorithms and software for energy sustainability on 24 January 2025 (co-supervision with Claire Monteleoni).
Interships
- Keshav Das with Amaury Durand and Julie Keisler - AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting
- Gaspard Berthelier - Explainability of electricity demand forecasting models: a Shapley value approach for positive component decomposition
- Thomas Le Corre with Nadia Oudjane and Ana Bušić
- Lucile Terras with Hui Yan - Bandit algorithms for hyper-parameter optimization
Teaching
I am currently in charge of the first year (Licence 3) at ISUP (Sorbonne University Institute of Statistics).
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[2025 - ] · Sorbonne Université, ISUP1 · Multivariate data analysis - Licence 3
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[2023 - ] · Sorbonne Université · Supervised research workshop in data science (Kaggle challenge) - Licence 1
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[2021 - ] · Sorbonne Université, ISUP - SCDI · Sequential statistical learning for time series forecasting - Master 2
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[2023 - 2025] · Sorbonne Université · Continuous Optimization, Python Tutorials - Licence 2
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[2019 - 2022] · ENSAE · Intervention in the statistical modeling seminar and project management - Master 1
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[2018 - 2021] · ENSAI · Semi-parametric regression models for electric load forecasting - Master 2
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[2017 - 2019] · Université Paris-Sud · Tutorial on probability and statistics - Licence 2
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[2017 - 2018] · Université Paris-Sud · Tutorial on probability - Licence 1 (PCSO)