Hernán Carrillo is a PhD student in computer science at Université de Bordeaux. He is part of the image and sound research team at LaBRI, and currently working in the PostProdLEAP project funded by the ANR (French National Agency for Research). His research interests include imaging inverse problems, deep learning, computational imaging and image and video processing.

His thesis focuses on developing new tools for video archive post-production by leveraging both, recent deep learning approaches and patch-based and variational approaches. More precisely, he designs deep learning models which include spatial and temporal regularization, and constraints on texture features as a way to automate the process of colorization on post-production videos and images.