About Me
I am an AI Research Scientist specializing in Deep Learning for time series and temporal data. My research explores the development of advanced neural architectures designed to capture and model complex temporal dependencies, with applications ranging from time series forecasting to representation learning.
Research Interests
- Deep learning for time series and spatio-temporal modeling
- Foundation models, large-scale pretraining and inference adaptation for time series
- Time series representation learning and self-supervised learning
- Imputation, forecasting, and other supervised tasks
- Scientific and industrial applications of AI
Publications & Talks
Explore my main research contributions here and discover my talks.
PhD Thesis
I hold a PhD in Deep Learning from Sorbonne University, where my research focused on Learning Neural Representations for Time Series.
📄 Read the manuscript
🖥️ View the defense slides
Contact
I’m always open to discussions about research and collaboration — feel free to get in touch!