Michaël Unser - CIBM | Center for Biomedical Imaging Michaël Unser - CIBM | Center for Biomedical Imaging

Michaël Unser

Michaël Unser

Head, CIBM SP EPFL Mathematical Imaging Section

Michaël Unser is professor and director of EPFL’s Biomedical Imaging Group, Lausanne, Switzerland. He is the head of the  CIBM Center for Biomedical Imaging Signal Processing Mathematical Imaging Section and he is the academic director  of the EPFL Center for Imaging.

His primary area of investigation is biomedical image processing. He is internationally recognized for his research contributions to sampling theory, wavelets, the use of splines for image processing, stochastic processes, and computational bioimaging. He has published over 400  journal papers on those topics. He is the author with P. D. Tafti of the book “An Introduction to Sparse Stochastic Processes,” Cambridge University Press 2014.  From 1985 to 1997, he was with the Biomedical Engineering and Instrumentation Program, National Institutes of Health, Bethesda, USA, conducting research on bioimaging.

Dr. Unser has served on the editorial board of most of the primary journals in his field, including the IEEE Transactions on Medical Imaging (Associate Editor-in-Chief 2003-2005), IEEE Transactions on Image Processing, Proceedings of IEEE, and SIAM Journal of Imaging Sciences. He is the founding chair of the technical committee on Bio Imaging and Signal Processing (BISP) of the IEEE Signal Processing Society.

Prof. Unser is a fellow of the IEEE (1999), an EURASIP fellow (2009), and a member of the Swiss Academy of Engineering Sciences. He is the recipient of several international prizes, including four IEEE-SPS Best Paper Awards and two Technical Achievement Awards from the IEEE (2008 SPS and EMBS 2010). He is frequently invited to deliver keynote presentations at international conferences, recent examples being ISBI’15, ICIP’15, ICASSP’16, EMBC’17, as well as tutorials.

Dr. Unser was awarded three ERC Advanced Researcher Grants : FUNSP (2011-2016), GlobalBioIm (2016-2021), and FunLearn (2021-2026).
KEYWORDS: Image reconstruction, Mathematical imaging, Inverse problems, Signal processing, Machine learning foundations