Thierry BOUWMANS is an Associate Professor at the University of La Rochelle (France) since 2000. He obtained the diploma of HDR for full professor position in 2014. His recent research interests consist mainly in the use of graph neural networks (GNNs) and graph signal processing (GSP) in the field of sound anomaly detection and moving objects detection in challenging environments. He has authored more than 150 papers in refereed international journals and conferences and has coauthored two books in CRC Press (background/foreground separation for video surveillance, robust PCA via decomposition in low rank and sparse matrices). His research investigated particularly the use of mathematical concepts (Statistical concepts, fuzzy concepts, Dempter-schäfer concepts), representation learning methods (discriminative subspace learning models, robust PCA), machine learning methods (GANs, GNNs) and graph signal processing. It also concerns full exhaustive surveys on mathematical tools used in foreground/background separation. He served as the Lead GE and co-GE in several special issues in IEEE (JSTP, Proceeding of IEEE, TCSVT), ACM (TOMM, TALLIP), ELSEVIER (PRL), and SPRINGER (MVA) journals. He is also the main organizer of the RSL-CV workshops hosted at ICCV (2015, 2017, 2019 and 2021) and the organizer of the workshop of " When Graph Signal Processing meets Computer Vision” at ICCV 2021. He has supervised seven PhD in this field. He is the creator and the administrator of the Background Subtraction Web Site (33 115 visits and 17 636 visitors). He is a reviewer for international journals including IEEE (Trans. on Image Processing, Trans. on Multimedia, Trans. on CSVT, etc.), SPRINGER (IJCV, MVA, etc.) and ELSEVIER (CVIU, PR, PRL, etc.), and top-level conferences such as CVPR, ICPR, ICIP, AVSS, ICASSP, etc. 

Claudia Isaza is a Professor at the Engineering Faculty of the Universidad de Antioquia, Medellín-Colombia since 2007.  She obtained titular professor category in 2021, and Senior investigator by the Ministry of Science, Technology, and Innovation – MinCiencias in 2019.  For over 12 years, she has been working on the automatic analysis of audio recordings to identify animal species and monitor changes in the ecosystem, with a particular focus on adapting fuzzy clustering and classification methods to biophony analysis, and more recently on using graph algorithms to represent ecosystem health based on soundscape analysis. In the field of learning algorithms applied to biological problems, she has authored 15 papers in peer-reviewed international journals and, over the past ten years, more than 15 conferences.   She has supervised two PhD. Students in this domain, eight Master students and more than ten undergraduate students. She has led, as the principal investigator, four projects related to bioacoustic analysis using machine learning. Additionally, she served as the principal investigator for a research program titled “Conservación biológica usando inteligencia artificial”. This work has consistently been conducted in collaboration with researchers from the fields of engineering, ecology and biology.  In this domain, she has collaborated with researchers from various academic and research institutions both nationally and internationally, including the Alexander von Humboldt Institute – Colombia (https://www.humboldt.org.co/), ITM University – Colombia (https://www.itm.edu.co/), MIA Laboratory – La Rochelle Université, France (http://mia.univ-larochelle.fr/), DIGILAB- Atarau Sanctuary- New Zealand (https://atarausanctuary.co.nz/sanctuary/link), CIBNOR – Mexico (https://www.cibnor.gob.mx/), and Rice University – USA (https://www.rice.edu/)

Anastasia Zakharova is an Associate Professor at the INSA Rouen Normandie (France) from 2011, and she is with University of La Rochelle (France) since 2018. Her research interests lie in the domain of graph neural networks (GNNs) and signal processing, with the emphasis on techniques of multiresolution analysis, wavelet decompositions, redundant decompositions, sparse representations and graph signal processing. She has supervised two PhD in this field of object detection. She is a reviewer for IEEE journals (TGRS, SPL) and ELSEVIER journals (PRL). She was an invited talk at workshops hold at ICME 2025 and ICIP 2025.

Since completing her PhD on the use of Passive Acoustic Monitoring for managing endangered fish species, Marta Bolgan has worked as a bio- and ecoacoustician for over a decade, first in academia and later in industry. She specializes in underwater acoustic recording and analysis to monitor species presence, behaviour, population dynamics, and biodiversity. At Fugro, she leads and coordinates the acoustic team in developing and delivering environmental acoustic services.