The skills of the Signal, Statistics and Learning (S2A) team are organized in four strategic themes, all relating to data analysis:
- 1. Machine learning
- 2. Probability and statistics
- 3. Signal processing and audio data analysis
- 4. Automatic analysis of social signals
Four strategic themes:
Machine learning is a field that lies at the interface of mathematics and computer science. It aims to develop concepts and algorithms for the automatic analysis of big data, usually for prediction purposes.
Machine learning group
Probability and statistics is a field that brings together all the techniques for the estimation and quantification of uncertainty, based on probabilistic modeling and statistical inference.
Probability and statistics group
Audio Data Analysis and Signal Processing is a field that relates to methods for data decomposition, representation learning and parametric modeling for audio signals and data in various applications such as source separation, musical information retrieval (MIR), the analysis of sound scenes, musical acoustics, the analysis of physiological signals, especially electroencephalographic (EEG) signals, and the transformation of audio signals.
Link to the ADASP website
Automatic analysis of social signals is a field that focuses on the computational models of social interaction analysis in web analytics, opinion analytics and social robotics.
Social computing group
Team members
- Stephan Clémençon, Professor, Team leader
- Florence d’Alché-Buc, Professor
- Roland Badeau, Associate Professor
- Pascal Bianchi, Professor
- Maria Boritchev, Associate Professor
- Chloé Clavel, Professor
- Bertrand David, Professor
- Slim Essid, Professor
- Olivier Fercoq, Professor
- Mathieu Fontaine, Associate Professor
- Ekhiñe Irurozki, Associate Professor
- Yann Issartel, Associate Professor
- Hicham Janati, Associate Professor
- Ons Jelassi, Chargée d’Enseignement et de Recherche
- Matthieu Labeau, Associate Professor
- Charlotte Laclau, Associate Professor
- Laurence Likforman, Associate Professor
- Pavlo Mozharovskyi, Associate Professor
- Geoffroy Peeters, Professor
- François Portier, Associate Professor
- Gaël Richard, Professor
- François Roueff, Professor
Associated members
- Gérard Blanchet, distinguished Professor
- Maurice Charbit, distinguished Professor
- Yves Grenier, distinguished Professor
- Patrice Bertail, invited Professor
(Professor at Paris X university) - Eric Moulines, invited Professor
(Professor at école Polytechnique) - Aurélien Bellet, invited Associate Professor
(Researcher INRIA Lille) - Romain Brault, invited Associate Professor
(Researcher Thalès R&T) - Stéphane Gentric, invited Associate Professor
(Researcher IDEMIA R&T) - Alexandre Gramfort, invited Associate Professor
(Researcher INRIA Saclay) - François Lainée, invited Associate Professor
(Geo4Cast)
PhD Students
- Manvi Agarwal
- Anass Aghbalou
- Achille Aknin
- Isaia Andrenacci
- Florian Angulo
- Louis Bahrman
- Alisa Barkar
- Dimitri Bouche
- Morgan Buisson
- Arturo Castellanos Salinas
- Mathis Chagneux
- Jean-Rémi Conty
- Tamim El Ahmad
- Antonin Gagneré-Debrincat
- Gan Qi
- Joël Garde
- Morgane Goibert
- Elio Gruttadauria
- Jeremy Guerin
- Yanzhu Guo
- Nathan Huet
- Marc Hulcelle
- Elie Kadoche
- Remi Leluc
- Mathieu Felix
- Luc Motte
- Jayneel Parekh
- David Perera
- Aurian Quelennec
- Alain Riou
- Emilia Siviero
- Lorraine Vanel
- Iyad Walwil
- Junjie Yang
- Salah Zaiem
Post-Docs
- James Cheshire
- Aina Gari Soler
- Quentin Legros
- Tuan Binh Nguyen
Engineers
- Joris Cosentino
- José Manuel Gil Panal
- Ignacio Laurenty
- Ariel Nora
- Aiwas Hussain Sani
- Romain Valla
- Changhong Wang
S2A Seminars
S2A Team latest news
Review: one year of research 2022
Faculty Members, Innovation — 13/06/2023The document depicts the great variety of scientific fields, research projects and applications generated by this abundant ecosystem.
IP Paris Doctoral School Awards
PhD — 16/12/2022Three Télécom Paris PhD students each received a poster prize at the IP Paris Doctoral School day on Dec. 13, 2022: Simon Delarue (Computing, Data and [...]
GRACE: Groups’ Analysis for automated Cohesion Estimation
Data Science & AI — 26/09/2022The project aims at developing computational models of cohesion among humans able to integrate the task and social [...]
Review: one year of research
Faculty Members, Innovation — 28/04/2022The generously illustrated 94-page document depicts the great variety of scientific fields, research projects and applications generated [...]
AI for sound: an ERC grant for prof. Gaël Richard
Data Science & AI, Faculty Members — 26/04/2022Professor Gaël Richard, executive director of Hi! Paris and Professor at Télécom Paris, an IMT school, [...]
A year of research and innovation
Faculty Members, Innovation — 10/03/2021The generously illustrated 84-page document depicts the great variety of scientific fields, research projects and applications [...]
Gaël Richard, IMT-Académie des Sciences Grand Prix
Faculty Members — 26/01/2021Voice synthesis, sound separation, automatic recognition of instruments or voices… His contributions to the academic [...]
Social robotics today and tomorrow: an overview
Design interaction perception, Faculty Members — 12/10/2020Chloé Clavel, Professor in Affective Computing at Télécom Paris, was involved in this talk about [...]
Why facial recognition algorithms can’t be perfectly fair
Digital Trust, Faculty Members — 20/07/2020By W. Maxwell and S. Clémençon. Facial recognition algorithms have been shown to be less accurate for [...]
Postdocs, a key stage in young researchers’ careers
PhD, Data Science & AI — 28/05/2020A postdoctoral position, or postdoc, represents a key opportunity for aspiring researchers to broaden their [...]