Full Professors

Roland Badeau
machine learning, data decomposition, machine listening, MIR
Pascal Bianchi
stochastic optimization
Philippe Ciblat
graphs, reinforcement learning, distributed processing
Stephan Clémençon
S2A team coordinator
machine learning, probability, statistics
Florence d'Alché-Buc
machine learning, interpretable and robust AI, kernel methods, structured prediction
Olivier Fercoq
optimization, stochastic algorithms, convex analysis
Pavlo Mozharovskyi
data detph, statistics, machine learning
Geoffroy Peeters
machine learning, machine listening, MIR
Gaël Richard
machine listening, MIR, machine learning, data decomposition, representation learning,
François Roueff
time series, statistics

 

Associate/Assistant Professors

Quentin Bouniot
deep learning, representation learning, explainability, robustness
Maria Boritchev
computational linguistics
Diego Di Carlo
spatial audio processing, physics-informed machine/deep learning
Radu Dragomir
optimization, theory of machine learning
Mathieu Fontaine
Bayesian methods, denoising, signal models, source separation, speech processing
Ekhiñe Irurozki
machine learning, rankings, preferences
Yann Issartel
mathematical statistics and machine learning
Ons Jelassi
distributed computing, large-scale data analysis
Matthieu Labeau
natural language processing, machine learning
Charlotte Laclau
machine learning, fairness, graphs
Laurence Likforman-Sulem
machine learning, handwriting analysis and recognition

 

Emeritus Professors

 

PhD Students

Pharoah Jardin
deep learning, MIR
deep learning, cover song indentification, music information retrieval
Kerrian le Caillec
Graph, Markov chains, Robust statistics deep learning, MIR
deep learning, cover song indentification, music information retrieval
Marius Rodrigues
machine learning, deep learning,
reverberation, hybrid deep learning, acoustics transfer
Hugo Malard
Isaia Andrenacci
machine learning for optical networks
Teysir Baoueb

generative models, diffusion models, audio signal processing
Clémentine Berger
deep learning,
Leonardo Boulitreau
Deep Learning, Machine Learning, Signal Processing, Singing Voice
Alicia Breidenstein
natural language processing
Arturo Castellanos
(robust) statistics
Louise Davy
bias and fairness in machine learning
Yann Choho
interpretable AI, natural language processing, representation learning
Thibaut de Saivre
deep learning, explainability, uncertainty quantification
Ikhlas Enaieh
machine learning, optimization
Antonin Gagneré
deep learning, representation learning, MIR
Qi Gan
human pose estimation, explainable ai
Joël Garde
optimization, optimal transport, inverse problems
Benoît Giniès
deep learning, representation learning, MIR
Gabriel Gros
optimization, optimal control, machine learning
Elie Kadoche
reinforcement learning
Liam Kelley
source separation, deep learning,
multichannel_source_separation, ambisonics
Paul Krzakala
optimal transports, graphs, deep learning
Zineb Lahrichi
signal models, deep learning
sound generation, controllable models
Louis Lalay
source separation, machine learning, signal processing, dereverberation
Haocheng Liu
machine listening,
Sicheng Mao
speech processing
Lilian Marey
machine learning, fairness, graphs
Gabriel Melo
Graph Supervised Learning, Optimal Transport, Kernel Methods
Victor Priser
stochastic optimization
Victor Manach
statistics, machine learning, fairness
Côme Peladeau
deep learning, MIR
Mathilde Perez
machine learning, fairness, graphs
Thomas Serre
Romain Therezien
Fairness, Explainable AI, Computer Vision
Bernardo Torres
deep learning, machine learning, representation learning,
Anna van Elst
machine learning, robustness, graphs
Bernardo Vieira de Miranda
deep learning, MIR
music generation, deep learning, performance alignment
Wen Yang
machine learning, point process, time series
Yerkin Yesbay
optimization, machine learning
Xuanyu Zhuang

 

Postdocs

Xiaoyu Bie
deep learning
James Cheshire
reinforcement learning, ranking
Michel Olvera
deep learning, machine listening
Sibsankar Singha
statistics and probability theory
Gayane Taturyan
Machine Learning, Fairness
Changhong Wang
deep learning, machine listening, MIR

 

Research Engineers

Igor Colin
decentralized learning, bandits, optimization, graphs
José Gil
machine learning, MIR
Quoc Duong Nguyen
deep learning, machine listening
Paraskevas Stamatiadis
speech processing,

 

Alumni & former members

Former Full Professors

Former Associate Professors

Former PhD Students

Former Postdocs