Samuel Kubler

Samuel Kubler is a young engineer in “Signal Processing & Image Analysis” graduated in September 2019 from ENSEEIHT (Toulouse). He is interested in Biomedical Image Processing, Machine Learning and Applied Mathematics for Biology and Medicine. He especially worked for Institut Universitaire de Cancérologie de Toulouse (IUCT) in Image Processing Algorithm for oncology, for IMACTIV-3D on skin characterization by OCT imagery or at Orange Labs – Caen in Machine Learning techniques to anonymize User Mobilities in a Big Data Context.
At Pasteur, he his currently working as a PhD student with Thibault Lagache and Jean-Christophe Olivo-Marin on the subject “Statistical methods for the robust extraction of objects’ spatio-temporal relations in bioimaging – Application to the functional analysis of neuronal networks in vivo”. Indeed, thanks to the improvement of calcium imagery techniques and new tracking algorithms, implementing robust statistical framework to correlate neural activities and create neural ensembles becomes fundamental to understand how brain integrates information and computes the animal’s state, especially in free-moving animals such as Hydra Vulgaris. In this respect, the robust extraction of objects’ spatio-temporal relationships appears as a cornerstone in the functional analysis of neuronal networks.

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