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
CH-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
EPFL > SB > SB-SMA > SMA-ENS

EPFL CIBM-SP
CH F1 622 (Bâtiment CH)
Station 6
CH-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
EPFL > SV > SV-SSV > SSV-ENS

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

EPFL IMAGING
BM 4142 (Bâtiment BM)
Station 17
CH-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 Programs

Doctoral Program in Photonics

Doctoral Program in Electrical Engineering

PhD Students

Aziznejad Shayan, Bohra Pakshal Narendra, Debarre Thomas Jean, Goujon Alexis Marie Frederic, Liu Yan, Lloréns Jover Icíar, Pham Thanh-An Michel, Pourya Mehrsa,

Past EPFL PhD Students

Aguet François , Arigovindan Muthuvel , Badoual Anaïs Laure Marie-Thérèse , Baritaux Jean-Charles , Bostan Emrah , Bourquard Aurélien , Chaudhury Kunal Narayan , Dehghani Tafti Pouya , Delgado Gonzalo Ricard , Donati Laurène , Fageot Julien René Pierre , Feilner Manuela , Guerquin-Kern Matthieu , Gupta Harshit , Horbelt Stefan , Jacob Mathews , Jonic Slavica , Kamilov Ulugbek , Khalidov Ildar , Kybic Jan , Liebling Michael Stefan Daniel , Luisier Florian , Munoz Barrutia Maria Arrate , Nilchian Masih , Pad Pedram , Püspöki Zsuzsanna , Ramani Sathish , Schmitter Daniel Andreas , Sühling Michael , 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.

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.

Signals and systems II (for MT)

This course is an introduction to the theory of discrete linear time invariant systems. Their properties and fundamental characteristics are discussed as well as the fundamental tools that are used to study and design them (Fourier transform, Z transform).

Signals and systems II (for SV)

This course is an introduction to the theory of discrete linear time invariant systems. Their properties and fundamental characteristics are discussed as well as the fundamental tools that are used to study and design them (Fourier transform, Z transform).

Image processing I

Introduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping in JAVA. 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 JAVA; application to real-world examples in industrial vision and biomedical imaging.