Edwin Carlinet

Edwin Carlinet is an Assistant Professor at EPITA Research Laboratory (LRE), specializing in mathematical morphology, hierarchical image representations, and high-performance computing. His research develops efficient algorithms for image processing with applications in document analysis and historical map vectorization.

Key projects include the SoDuCo initiative extracting data from 19th-century Parisian trade directories and parallel implementations of morphology algorithms. He leads development of the Pylene image processing library, focusing on generic and efficient implementations.

Teaching covers parallel programming, data compression, C++, and GPU programming at EPITA, alongside bioinformatics courses at Sup'Biotech. Research supervision includes PhD candidates working on modern implementations of mathematical morphology algorithms and noise estimation techniques.

Recent publications focus on optimizing computational workflows for historical document processing, including noise impact analysis on morphological structures and GPU acceleration of max-tree computation.