Benjamin Ricaud has a PhD in Mathematical Physics from the University of Toulon France (2007). Previously, he has been a researcher at the Laboratory of Mechanics and Acoustics, Marseilles, the Center of Theoretical Physics, Marseilles, the CEA Cadarache and the LATP (Math Institute) Marseilles.
From 2012 to 2016 he held a research position at EPFL within the LTS2 lab. In 2016 he founded a startup specialized in data science Evia cybernetics. He is now a research scientist back in the LTS2 since January 2018.
His actual research is focused on networks, data analysis on networks and the understanding/tracking of dynamic activity over networks.
Analysis of graphs and networks
Dynamic activity over networks
Theoretical concepts and methods for the extraction of information from data with a graph structure
Signal and image processing
Fields of expertise
Signal processing on graphs
Publications with EPFL
P. Vandergheynst; B. Ricaud; K. Benzi ; System, device, and method for contextual knowledge retrieval and display. WO2017187401 . 2017.
J. Paratte / P. Vandergheynst (Dir.) : Graph-based Methods for Visualization and Clustering. Lausanne, EPFL, 2017. DOI : 10.5075/epfl-thesis-7952.
A. Griffa; B. Ricaud; K. Benzi; X. Bresson; A. Daducci et al. : Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems; Neuroimage. 2017. DOI : 10.1016/j.neuroimage.2017.04.015.
K. Smith; B. Ricaud; N. Shahid; S. Rhodes; J. M. Starr et al. : Locating Temporal Functional Dynamics of Visual Short-Term Memory Binding using Graph Modular Dirichlet Energy; Scientific reports, Nature. 2017. DOI : 10.1038/srep42013.
H. Lachambre; B. Ricaud; G. Stempfel; B. Torresani; C. Wiesmeyr et al. : Optimal Window and Lattice in Gabor Transform. Application to Audio Analysis.. 2016. 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), Timisoara, ROMANIA, SEP 21-24, 2015. p. 109-112. DOI : 10.1109/Synasc.2015.25.
F. Grassi; N. Perraudin; B. Ricaud : Tracking Time-Vertex Propagation using Dynamic Graph Wavelets. 2016. 4th IEEE Global Conference on Signal and Information Processing, Washington D.C., USA, December 7–9, 2016.
M. G. Rasmussen; B. Ricaud; B. Savoie : On the optical properties of carbon nanotubes. Part I. A general formula for the dynamical optical conductivity; Journal Of Mathematical Physics. 2016. DOI : 10.1063/1.4940135.
K. Benzi; B. Ricaud; P. Vandergheynst : Principal Patterns on Graphs: Discovering Coherent Structures in Datasets; IEEE Transactions on Signal and Information Processing over Networks. 2016. DOI : 10.1109/TSIPN.2016.2524500.
N. Shahid; N. Perraudin; V. Kalofolias; B. Ricaud; P. Vandergheynst : PCA using graph total variation. 2016. 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Shanghai, China, 20-25 March 2016. p. 4668-4672.
D. Shuman; B. Ricaud; P. Vandergheynst : Vertex-Frequency Analysis on Graphs; Applied And Computational Harmonic Analysis. 2016. DOI : 10.1016/j.acha.2015.02.005.
K. Benzi; A. Griffa; B. Ricaud; P. Vandergheynst; J.-P. Thiran et al. : Dynamic activation patterns in brain MRI data. 2015. 25th Colloque Gretsi, Lyon.
A. Griffa; K. Benzi; B. Ricaud; X. Bresson; P. Vandergheynst et al. : Mapping resting-state dynamics on spatio-temporal graphs: a combined functional and diffusion MRI approach. 2015. 23rd International Symposium on Magnetic Resonance in Medicine (ISMRM), Toronto.
B. Ricaud; G. Stempfel; B. Torresani; C. Wiesmeyr; H. Lachambre et al. : An optimally concentrated Gabor transform for localized time-frequency components; Advances In Computational Mathematics. 2014. DOI : 10.1007/s10444-013-9337-9.
B. Ricaud; B. Torresani : A survey of uncertainty principles and some signal processing applications; Advances In Computational Mathematics. 2014. DOI : 10.1007/s10444-013-9323-2.
B. Ricaud; D. I. Shuman; P. Vandergheynst : On the Sparsity of Wavelet Coefficients for Signals on Graphs. 2013. Conference on Wavelets and Sparsity XV. DOI : 10.1117/12.2022850.
B. Ricaud; B. Torresani : Refined Support and Entropic Uncertainty Inequalities; Ieee Transactions On Information Theory. 2013. DOI : 10.1109/Tit.2013.2249655.
D. Shuman; B. Ricaud; P. Vandergheynst : A Windowed Graph Fourier Transform. 2012. Statistical Signal Processing Workshop, Ann Arbor, Michigan, USA, August 5-8, 2012. p. 133-136.
F. Grassi; A. Loukas; N. Perraudin; B. Ricaud : A Time-Vertex Signal Processing Framework; IEEE Transactions on Signal Processing.
N. Perraudin; B. Ricaud; D. I. Shuman; P. Vandergheynst : Global and Local Uncertainty Principles for Signals on Graphs; Applied and Computational Harmonic Analysis.
D. Shuman; B. Ricaud; P. Vandergheynst : A Windowed Graph Fourier Transform. IEEE Statistical Signal Processing Workshop, Ann Arbor, Michigan, USA, August 5-8, 2012.