École Normale Supérieure de Paris-Saclay - PhD, Machine Learning, 2027 (expected).
CIFRE PhD thesis in collaboration with EDF on Graphical Models for Joint Forecasting of Short-Term Consumption and Renewable Production.
Supervisors: A. Kalogeratos (ENS PS), M. Mougeot (ENS PS) and Y. Amara-Ouali (EDF).
École Normale Supérieure de Paris-Saclay - MSc, MVA, Machine Learning and Computer Vision, 2023.
Learning for Time Series, Statistical Learning, Optimization, Topological Data Analysis, Image Denoising, Remote Sensing Data, Responsible Machine Learning. High honors.
Télécom SudParis - BSc and MSc, Mathematics and Computer Science, 2023.
Analysis and Theory of Integration, Statistics and Data Analysis, Optimization, Probability, Signal and Communication Theory, Scientific Computing, Bayesian Estimation in Markov Models, Data Mining, Algorithms and Programming Languages, Operating Systems. GPA: 3.86/4.
University of Twente - Erasmus exchange, Mathematics, 2022.
Data Science, Deep Learning, Reinforcement Learning, Differential Privacy, Uncertainty Quantification and Data-driven Modeling, Mixed-Integer Optimization.
Research Intern in Machine Learning, EDF and Centre Borelli, 2023.
Development of a short-term electricity demand forecasting methodology using Graph Neural Networks taking into account geolocalized and regional/individual electricity consumption data sources. Thesis available here.
Supervisors: Y. Amara-Ouali (EDF), Q. Chan-Wai-Nam (EDF) and A. Kalogeratos (ENS PS).
Data Science Intern, Okwind, 2022.
Optimization of a solar production prediction algorithm using artificial intelligence. Several time series models were tested and optimized: NeuralProphet, NHiTS, DeepAR and TemporalFusionTransformer.
Supervisor: T. Riou.
Software Development Intern, Aerometrik, 2021.
Development of Arduino programs to interact with particle counters.
Supervisor: D. Rouault.