Hervé Bourlard

EPFL STI SEL-GE
ELE 130 (Bâtiment ELE)
Station 11
CH-1015 Lausanne

EPFL AVP-PGE EDEE-ENS
ELB 112 (Bâtiment ELB)
Station 11
CH-1015 Lausanne

EPFL STI-DO
BM 4101 (Bâtiment BM)
Station 17
CH-1015 Lausanne

Office: BM 4101
EPFL > STI > STI-DEC > PH-STI

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Administrative data

Teaching & PhD

Teaching

Electrical and Electronics Engineering

PhD Programs

Doctoral Program in Electrical Engineering

PhD Students

Janbakhshi Parvaneh, Kabil Selen Hande, Schnell Bastian, Vyas Apoorv,

Past EPFL PhD Students

Ajmera Jitendra , Aradilla Guillermo , Asaei Afsaneh , Atanasoaei Cosmin , Ba Silèye Oumar , Babu Saheer Lakshmi , Bala Subburaman Venkatesh , Barnard Mark , Benzeghiba Mohamed Faouzi , Chen Datong , Chingovska Ivana , Da Silva Quelhas Pedro Manuel , De Freitas Pereira Tiago , Dey Subhadeep , Dighe Pranay , Dimitrakakis Christos , Dubagunta Subrahmanya Pavankumar , El Shafey Laurent , Favre Sarah , Fornoni Marco , Grangier David , Habibi Maryam , Hagen Astrid , Heusch Guillaume , Honnet Pierre-Edouard Jean Charles , Ikbal Shajith , Imseng David , Jaquier Noémie Laure Gwendoline , Just Agnès , Keller Mikaela , Ketabdar Hamed , Kuzborskij Ilja , Lathoud Guillaume , Lebret Rémi Philippe , Legrand Joël Yvon Roland , Liang Hui , Luo Jie , Magimai Doss Mathew , Mesot Bertrand , Meyer Thomas , Miculicich Werlen Lesly Sadiht , Misra Hemant , Mohammadi Amir , Mohammadi Gelareh , Monay Michaud Florent , Muckenhirn Hannah , Oliveira Pinheiro Pedro Henrique , Paiement Jean-François , Palaz Dimitri , Pappas Nikolaos , Parthasarathi Sree Hari Krishnan , Pignat Emmanuel , Pinto Joel Praveen , Poh Norman Hoon Thian , Pozdnoukhov Alexei , Pu Xiao , Ram Dhananjay , Rasipuram Ramya , Razavi Marzieh , Rodriguez Yann , Roy Anindya , Sapru Ashtosh , Scaringella Nicolas , Smith Kevin , Stephenson Todd , Taghizadeh Mohammadjavad , Tanwani Ajay Kumar , Tommasi Tatiana , Tong Sibo , Ullmann Raphaël Marc , Vijayasenan Deepu , Weber Katrin , Yazdani Majid , Yella Sree Harsha , Zhang Dong ,

Courses

Statistical Sequence Processing

This course discusses advanced methods extensively used for the processing, prediction, and classification of temporal (multi-dimensional and multi-channel) sequences. In this context, it also describes key links between signal processing, linear algebra, statistics and artificial neural networks.