Pierre Comon is affiliated with Grenoble Alpes University in France. Their research spans the intersection of Mathematics, Computer Science, and Engineering, with a focus on specialized subfields such as Computational Mathematics, Computational Mechanics, Statistics and Probability, Computer Vision and Pattern Recognition, and Signal Processing.
The scientist's research topics primarily address tensor decomposition and applications, sparse and compressive sensing techniques, blind source separation techniques, image and signal denoising methods, matrix theory and algorithms, advanced neuroimaging techniques and applications, and advanced chemical sensor technologies.
Recent publications by Pierre Comon include the following papers:
Frequent collaborators include Konstantin Usevich, David Brie, Pierre Maho, Cyril Herrier, and Thierry Livache.
Pierre Comon's work has been published in various venues, including:
The scientist has been recognized as an IEEE Fellow in 2007 for contributions to high-order statistics and blind techniques for signal processing.
In 2019, Pierre Comon was named a SIAM Fellow for pioneering contributions to signal processing, tensor decompositions, and independent component analysis.
Pierre Comon
Pierre Comon;Christian Jutten
P. Comon;G.H. Golub
Pierre Comon;Gene Golub;Lek-Heng Lim;Bernard Mourrain
Pierre Comon;Christian Jutten;Jeanny Herault
P. Comon;X. Luciani;A. L. F. de Almeida
Pierre Comon
Pierre Comon
V. Zarzoso;P. Comon
A. Kachenoura;L. Albera;L. Senhadji;P. Comon
Myriam Rajih;Pierre Comon;Richard A. Harshman
P. Chevalier;L. Albera;A. Ferreol;P. Comon
P. Comon;B. Mourrain
Jérôme Brachat;Pierre Comon;Bernard Mourrain;Elias P. Tsigaridas;Elias P. Tsigaridas
Jean-Louis Lacoume;Pierre-Olivier Amblard;Pierre Comon
Lek-Heng Lim;Pierre Comon
Pierre Comon
P. Comon
P. Comon
Yang Xu;Zebin Wu;Jocelyn Chanussot;Pierre Comon
Myriam Rajih;Pierre Comon
If you think any of the details on this page are incorrect, let us know.
For students pursuing Mathematics in the USA, exploring related online degrees can open doors to diverse career paths. Business and finance fields particularly benefit from strong analytical skills, making degrees like an MBA or a Master’s in Finance attractive options for math graduates.
If you are considering a business-focused degree, several programs stand out for their accessibility and affordability. Those interested in manageable admissions might look at the easiest mba program to get into, which can provide a smoother transition into graduate business studies.
Additionally, the easiest mba programs offer flexible online formats that accommodate working students, allowing math graduates to apply their quantitative skills efficiently in management and strategy roles.
For those aiming for specialized business leadership, exploring one of the most affordable online dba programs can be a cost-effective way to advance into executive roles while leveraging a strong math foundation.
Finance-focused students may also find value in pursuing one of the cheapest masters in finance, which combines quantitative training with financial expertise to prepare for careers in investment banking, risk analysis, or financial planning.
Monash University
Konkuk University
National University of Singapore
The Ohio State University
Kyoto University
Cincinnati Children's Hospital Medical Center
University of Aberdeen
Imperial College London
International Centre for Genetic Engineering and Biotechnology
National Institutes of Health
University of Naples Federico II
Chinese Academy of Sciences
Kyushu University
Temple University
Colorado State University
Radboud University