Éric Moulines was born in Bordeaux on January 24, 1963. He is a French researcher who studies statistical learning and signal processing. In 2010, he received the silver medal from the French National Center for Scientific Research (CNRS). In 2011, he was awarded the France Télécom prize, which is given in partnership with the French Academy of Sciences. In 2012, he became a Fellow of the European Association for Signal Processing. In 2016, he was named a Fellow of the Institute of Mathematical Statistics. He is also a General Engineer of the Corps des Mines, class of 1981 (X81).
Biography
Éric Moulines entered École polytechnique in 1981, then studied at Télécom ParisTech.
He began his career at the Centre national d'études des télécommunications, where he worked on creating speech from written words. He helped develop new methods for creating sound waves, known as PSOLA (pitch synchronous overlap and add).
After completing his thesis in 1990, he became a lecturer at École Nationale Supérieure des Télécommunications. He then focused on problems related to statistical signal processing. He contributed to techniques for identifying systems with multiple variables and separating different sources of signals. He also created new methods for adjusting systems based on changing conditions.
In 2006, he was authorized to direct research and became a professor at Télécom Paris. He then focused on applying Bayesian methods in signal processing and statistics.
Éric Moulines directed 21 theses, was president of the jury for 9 theses, was a reviewer for 10 theses, and was a member of the jury for 6 theses.
Scientific work
He is interested in understanding hidden patterns in data using models like hidden Markov chains and non-linear state models, which involve tracking changes over time. He focuses on methods that use groups of particles to improve filtering techniques. He also studies how to analyze models where not all information is available, combining estimation and simulation with Monte Carlo Markov Chain Methods (MCMC). He has created many tools to study how MCMC methods reach stable results and how Markov chains behave over long periods.
Since 2005, he has worked on problems related to learning from data, including studying algorithms that use randomness to solve optimization challenges.
In 2015, he became a professor at the Centre de mathématiques appliquées de l'École polytechnique. His research includes using Bayesian methods with large models to address uncertainty in statistical learning.
Honours and awards
- Chosen as a member of the French Academy of Sciences in 2017
- Received the CNRS Silver Medal in 2010
- Named an Officer of the Palmes Académiques