History of the laboratory

I developed my first research activities in the image processing and pattern recognition laboratory (TIRF), which became, in January 1998, a joint unit of CNRS, the images and signals laboratory (LIS), by merging two laboratories, TIRF and CEPHAG. In January  2007, by merging of three laboratories: LIS, LAG (Automatic control lab.) and ICP (Speech lab.), is born the large laboratory GIPSA-lab.

I first worked under the supervision of Prof. Jeanny Hérault on modelisation of neural networks and design of artificial neural networks algorithms, with applications in signal and ilmage processing. Since end of 80's, I develop my own research activities, with my PhD students and collaborators, mainly on source separation and independent component analysis (ICA), sparse representation and their applications.

 After theoretical contributions on linear instantaneous mixtures (from 1984), convolutive mixture (from 1987, but especially after 1990), I was interested by source separation in nonlinear mixtures (especially from 1996). In addition, under the impulse of my colleague and friend, Prof. Massoud Babaie-Zadeh from Sharif University of Technology (Tehran, Iran), I also addressed sparse representation and sparse sourse separation in under-determined mixtures since 2008.

Since 1981, my research activities are focused on statistical signal processing issues strongly related with machine learning. Very early, I investigated artificial neural networks, how they process information. For understanding how vertebrate brain are able to code/decode their own motions, with Prof. J. Hérault and Dr. B. Ans, I developped the concept of source separation and contributed in its theoretical fundations. I also applied the results in many applications, especially in audio-visual source separation, in biomedical engineering (ECG, EEG, etc.), hyperspectral imaging and chemical sensing. More recently, I investigated sparse representations, dictionary learning, and data fusion from a theoretical perspective in the framework of Big Data, which are typically multimodal, heterogeneous, high-dimension, with again applications in brain imaging, remote sensing, chemical sensor array, etc. With Dr. M. Congedo, I also work on brain-computer interfaces, and especially in representation and processing on Riemanian manifolds.

During the last past 6 years, I mainly worked with the support of European Research Council, with an ERC Advanced Grant for the project Challenges on Extraction and Separation of sources (CHESS). The three main challenges are:

• Source separation for multimodal recordings;
• Source separation for nonlinear mixtures;
• Source separation with data in very large or very small dimensions.

A summary of the results obtained during this project can be found in the final CHESS project report.

The main applications I currently address, and which are necessary both for validating theoretical results and for raising new relevant issues with realistic assumptions, are the following:

Team and Cooperations