Pierre Borgnat

Pierre Borgnat is a CNRS Research Professor at École Normale Supérieure de Lyon, leading the Signals, Systems & Physics group. His research integrates signal processing, graph theory, and machine learning for complex data analysis.

Key contributions include:

• Multiscale methods for graph signals and networks
• Time-frequency analysis of nonstationary data
• Applications in transportation, neuroscience, and climate science
• Graph-based learning with optimal transport

He directs the 'Signals, Systems & Physics' group and serves as Area Editor for IEEE Transactions on Signal Processing. Recent projects include ACADEMICS (machine learning for complex models) and climate extremes forecasting.