Michaël Unser

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Full Professor

michael.unser@epfl.ch +41 21 693 51 75 http://bigwww.epfl.ch/unser/index.html

+41 21 693 51 75
Office:  BM 4136
EPFL > VPA > VPA-AVP-PGE > AVP-PGE-EDOC > EDEE-ENS

EPFL STI IMT LIB
BM 4136 (Bâtiment BM)
Station 17
1015 Lausanne

+41 21 693 51 75
+41 21 693 11 85
Office:  BM 4136
EPFL > STI > IEM > LIB

Web site:  Web site:  https://bigwww.epfl.ch/

+41 21 693 51 75
Office:  BM 4136
EPFL > SB > SB-SMA > SMA-ENS

Web site:  Web site:  https://sma.epfl.ch/

EPFL CIBM-SP
CH F0 622 (Bâtiment CH)
Station 6
1015 Lausanne

+41 21 693 51 75
Office:  BM 4136
EPFL > VPA > VPA-AVP-CP > CIBM > CIBM-SP

Web site:  Web site:  https://www.cibm.ch/

+41 21 693 51 75
Office:  BM 4136
EPFL > SV > SV-SSV > SSV-ENS

Web site:  Web site:  https://sv.epfl.ch/education

EPFL IMAGING
BM 4142 (Bâtiment BM)
Station 17
1015 Lausanne

+41 21 693 51 75
Office:  BM 4136
EPFL > VPA > VPA-AVP-CP > IMAGING > IMAGING-GE

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Administrative data

Fields of expertise

Image Processing Medical Imaging Biological Imaging Wavelets Splines Multiresolution

Teaching & PhD

Teaching

Microengineering

Mathematics

PhD Students

Bohra Pakshal Narendra, Ducotterd Stanislas, Goujon Alexis Marie Frederic, Guillemet Vincent Patrick Lawrence, Liu Yan, Pourya Mehrsa,

Past EPFL PhD Students

Aguet François , Aziznejad Shayan , Badoual Anaïs Laure Marie-Thérèse , Baritaux Jean-Charles , Bostan Emrah , Bourquard Aurélien , Chaudhury Kunal Narayan , Debarre Thomas Jean , Dehghani Tafti Pouya , Delgado Gonzalo Ricard , Donati Laurène , Fageot Julien René Pierre , Guerquin-Kern Matthieu , Gupta Harshit , Kamilov Ulugbek , Khalidov Ildar , Luisier Florian , Nilchian Masih , Pad Pedram , Pham Thanh-An Michel , Püspöki Zsuzsanna , Ramani Sathish , Schmitter Daniel Andreas , Uhlmann Virginie Sophie , Vonesch Cédric René Jean ,

Courses

Sparse stochastic processes

We cover the theory and applications of sparse stochastic processes (SSP). SSP are solutions of differential equations driven by non-Gaussian innovations. They admit a parsimonious representation in a wavelet basis and are relevant to coding, compressed sensing, and biomedical imaging.

Fundamentals of Image Analysis

This summer school is an hands-on introduction on the fundamentals of image analysis for scientists. A series of lectures provide students with the key concepts in the field, and are followed by practical sessions with popular software on the participants' own image-analysis software.

Signals and systems I (for MT)

Introduction of the basic concepts and mathematical tools for the characterization of signals and for the analysis and design of linear systems (filters or transmission channels). Application of these techniques to signal processing and communications.

Signals and systems I (for SV)

Introduction of the basic concepts and mathematical tools for the analysis and characterization of signals, the design of processing algorithms, and the linear modeling of systems for students in the life sciences. Application of these techniques to signal processing and communications.

Image processing I

Introduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping using Jupyter notebooks. Application to real-world examples in industrial vision and biomedical imaging.

Image processing II

Study of advanced image processing; mathematical imaging. Development of image-processing software and prototyping in Jupyter Notebooks; application to real-world examples in industrial vision and biomedical imaging.