Alexandre BENOIT

Alexandre BENOIT is a Professor at Polytech Annecy-Chambéry, Université Savoie Mont-Blanc, and a permanent member of the LISTIC laboratory. His research focuses on deep learning, federated learning, computer vision, remote sensing, and explainable AI, with applications in astrophysics, environmental monitoring, and healthcare. He leads projects on glacier modeling, federated learning bias mitigation, and satellite image analysis.

His teaching activities include courses on deep learning (TensorFlow/PyTorch), image processing (Matlab/OpenCV), and programming (C/C++/Python) at undergraduate and graduate levels. He has supervised over 10 PhD students and collaborates with industries like Total, Renault, and startups on AI integration.

Research highlights include developing the GammaLearn framework for Cherenkov Telescope Array data analysis and bio-inspired retina models integrated into OpenCV. He co-organized major conferences such as CBMI 2012 and EUSFLAT 2011, and serves on editorial boards for IEEE Transactions on Image Processing and other journals.

Current projects address federated learning fairness, glacier thickness estimation via deep learning, and oil slick detection using SAR imagery. His work emphasizes frugal models, physically informed AI, and ethical AI practices in collaborative environments.