Daniel Sage

Daniel Sage is a Lecturer and Scientific Advisor at École polytechnique fédérale de Lausanne (EPFL), affiliated with the Biomedical Imaging Laboratory (LIB) under the College of Engineering (STI) and School of Life Sciences (SV). He specializes in bioimage informatics, structured-illumination microscopy, and deep learning applications for biomedical imaging. His work spans algorithm development for single-molecule localization microscopy (SMLM), fluorescence imaging, and 3D reconstruction.

His research group has developed open-source tools like FlexSIM for light inhomogeneity correction, DeepImageJ for integrating deep learning in ImageJ, and Steer'n'Detect for orientation-accurate template detection. His publications focus on correcting multiple-blinking artifacts in PALM, optimal transport metrics for SMLM evaluation, and contextual feature analysis for xenograft cell classification.

He mentors PhD students and contributes to interdisciplinary education through courses such as Bioimage Informatics and Fundamentals of Image Analysis, emphasizing practical software solutions and Java programming for bioimage processing. His collaborations include institutions like Howard Hughes Medical Institute and Centre National de la Recherche Scientifique (CNRS).