L'IA pour tous
Le programme de recherche l’IA pour Tous veille à ce que l’intelligence artificielle serve l’ensemble des personnes, quels que soient leur origine ou leur situation. Nos recherches développent une IA équitable et participative en plaçant les individus – en particulier les communautés sous-représentées – au centre de sa conception et de son déploiement.
Nous créons des plateformes interactives ainsi que de nouvelles techniques d’échantillonnage et d’analyse de données qui reflètent la diversité des populations, tout en favorisant des communautés durables et connectées à l’échelle mondiale. En permettant aux individus de co-concevoir et d’utiliser les algorithmes d’IA tout au long du cycle de développement, nous faisons évoluer le paradigme, passant de simples utilisateurs passifs à des participants actifs.
Nos travaux font également progresser le discours public inclusif grâce à des innovations dans la prise de décision collaborative et le vote électronique, en réinventant l’IA comme un outil de progrès sociétal transparent, interprétable et inclusif.
Domaines d’application
- Gouvernance éthique, Responsabilité & Services publics
- Engagement civique, Démocratie & Discours public
- Prise de décision collaborative
- IA et technologies d’assistance pour la littératie numérique, le développement des compétences et l’inclusion
- Systèmes d’IA culturellement inclusifs
Domaines d'expertise
- Bio-informatique & Informatique de la santé
- Science des données & Informatique sociale
- Interaction homme–machine
- Imagerie & Vision par ordinateur
- Apprentissage automatique
- Traitement automatique du langage naturel
- Robotique & Systèmes autonomes
- Sécurité & Protection de la vie privée
- Traitement du signal
- Traitement de la parole & du signal audio
Ce programme contribue aux ODD des Nations-Unies suivants
Personnes
ABBET, Philip
(Senior Research and Development Engineer)
- website
AGRAWAL, Sanat (Kumar)
(Research Intern)
AL AMINE, Zeina
(Research Assistant)
ALONSO DEL BARRIO, David
(Research and Development Engineer)
AMIRI, Mahdi
(Doctoral Researcher)
ANNAPUREDDY, Ravinithesh Reddy
(Doctoral Researcher)
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BAÑERAS-ROUX, Thibault
(Postdoctoral Researcher)
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BAROUDI, Séverin
(Research Intern)
BEN MAHMOUD, Imen
(Research and Development Engineer)
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BHATTACHARJEE, Sushil (Kumar)
(Research Associate)
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BORNET, Olivier
(Head of Research and Development Team)
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BROS, Victor
(Doctoral Researcher)
BURDISSO, Sergio (Gastón)
(Research Associate)
CANÉVET, Olivier
(Senior Research and Development Engineer)
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CARRON, Daniel
(Senior Research and Development Engineer)
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CLIVAZ, Guillaume
(Senior Research and Development Engineer)
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COLBOIS, Laurent
(Postdoctoral Researcher)
COMAN, Andrei (Catalin)
(Doctoral Researcher)
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DAYER, Yannick (Nicolas)
(Senior Research and Development Engineer)
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DROZ, William
(Senior Research and Development Engineer)
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ECABERT, Christophe
(Research Associate)
EL HAJAL, Karl
(Doctoral Researcher)
EL ZEIN, Dina
(Doctoral Researcher)
ESPINOSA MENA, Jose Rafael
(Doctoral Researcher)
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GAIST, Samuel
(Senior Research and Development Engineer)
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GATICA-PEREZ, Daniel
(Senior Research Scientist with Academic Title)
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GATTI, Martina
(Research Intern)
GEORGE, Anjith
(Research Associate)
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HENDERSON, James (Brinton)
(Senior Research Scientist)
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HERMANN, Enno
(Postdoctoral Researcher)
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HOU, Mingchi
(Doctoral Researcher)
HOVSEPYAN, Sevada
(Research Associate)
KALOGA, Yacouba
(Postdoctoral Researcher)
KAYAL, Salim
(Senior Research and Development Engineer)
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KODRASI, Ina
(Research Scientist)
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KOMATY, Alain
(Research Associate)
KOTWAL, Ketan
(Research Intern)
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KRIVOKUĆA HAHN, Vedrana
(Research Associate)
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KULKARNI, Ajinkya (Vijay)
(Postdoctoral Researcher)
KUMAR, Shashi
(Doctoral Researcher)
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LI DONG, Virgílio
(Apprentice)
LUÉVANO GARCÍA, Luis Santiago
(Postdoctoral Researcher)
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MACEIRAS, Jérémy
(Senior Research and Development Engineer)
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MAGIMAI DOSS, Mathew
(Senior Research Scientist)
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MARCEL, Christine
(Senior Research and Development Engineer)
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MARCEL, Sébastien
(Senior Research Scientist with Academic Title, Interim management team)
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MAYORAZ, André
(Research and Development Engineer)
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MICHEL, Samuel
(Research and Development Engineer)
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MOHAMMADI, Amir
(Research and Development Engineer)
MOTLICEK, Petr
(Senior Research Scientist)
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NANCHEN, Alexandre
(Senior Research and Development Engineer)
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OTROSHI SHAHREZA, Hatef
(Postdoctoral Researcher)
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OUTUMURO BUENO, Alberto
(Research Assistant)
ÖZTÜRK, Ünsal
(Postdoctoral Researcher)
PRASAD, Amrutha
(Postdoctoral Researcher)
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PUROHIT, Tilak
(Research Intern)
RAHIMI NOSHANAGH, Parsa
(Doctoral Researcher)
SANCHEZ-CORTES, Dairazalia
(Postdoctoral Researcher)
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SHIRAKAMI, Haruki
(Doctoral Researcher)
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SINGH VIRK, Renuka
(Research Intern)
ULUCAN, Ibrahim
(Research Assistant)
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VERZAT, Colombine
(Senior Research and Development Engineer)
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VIDIT, Vidit
(Postdoctoral Researcher)
VILLATORO TELLO, Esaú
(Research Associate)
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WATAWANA, Hasindri (Sankalpana)
(Doctoral Researcher)
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ZANGGER, Alicia
(Research and Development Engineer)
- website
Publications choisies
Generalization and Personalization of Passive Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries, L. Meegahapola, W. Droz, P. Kun, A. de Gotzen, C. Nutakki, S. Diwakar, S. Ruiz Correa, D. Song, H. Xu, M. Bi-doglia, G. Gaskell, A. Chagnaa, A. Ganbold, T. Zundui, C. Caprini, D. Miorandi, A. Hume. In Proc. of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Tech-nologies (PACM IMWUT), 6(4), pp. 1-32, Dec. 2022.
A multidisciplinary approach with a large international team to quantify the perfor-mance of inference models for real-life smartphone sensor data, investigating coun-try-specific, country-agnostic, and multi-country approaches. This work is an exam-ple of progress towards the development of diversity-aware algorithms for people in eight countries in Europe, Latin America, and Asia, and received an ACM IMWUT Distinguished Paper Award in 2023.
Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and BERT Models for Maltese, Kurt Micallef, Albert Gatt, Marc Tanti, Lonneke van der Plas and Claudia Borg, in Proceedings of the workshop on Deep Learning for Low-Resource NLP, 2022.
Technological tools are missing for many languages in the world. This paper com-pares methods for creating language technologies for a language that has limited resources: Maltese. We also present a newly created collection of texts for Maltese, that results in state-of-the-art performance on several language tasks, despite the fact that the new collection of text is much smaller than those typically used for high-resourced languages.
Towards Accessible Sign Language Learning and Assessment, Neha Tarigopula, San-drine Tornay, Skanda Muralidhar, Mathew Magimai-Doss, ACM International Con-ference on Multimodal Interaction, 2022.
Sign language recognition benefits from depth information provided by sensors like Kinect. To scale this up, we need to reduce the dependency on such sensors, which are not accessible to everybody, and develop webcam-based solutions. This paper in-vestigates sign language recognition and assessment in 2D space. Experiments show that, while loss of depth information leads to drops in recognition performance, high performance of sign language assessment can still be obtained.
Projets choisis
AI4MEDIA, 2020-2024, H2020, GATICA-PEREZ: A EUROPEAN EXCELLENCE CENTRE FOR MEDIA, SOCIETY AND DEMOCRACY
This project aims to deliver core AI advances and training to serve the media sector, while ensuring that European values of ethical and trustworthy AI are embedded in future deployments. In particular, we study phenomena related to European local news, with emphasis on human-centered AI methods to understand both local news content and local user perceptions.
UNIDIVE, 2022-2026, COST ACTION, VAN DER PLAS: UNIVERSALITY, DIVERSITY AND IDIOSYNCRASY IN LANGUAGE TECHNOLOGY
Recognizing that progress in natural language processing (NLP) needs to account for and foster language diversity, this network aims to provide theoretical models and practical advances about language universality and diversity, including language resources and tools covering a large variety of language phenomena in many languages, including those who are currently low-resourced and endangered.
FAIRMI, 2023-2026, SNSF, ANJOS: MACHINE LEARNING FAIRNESS WITH APPLICATION TO MEDICAL IMAGES
In medical imaging, the use of machine learning (ML) models to support large scale screening and diagnosis has substantially increased. However, the study of demographic bias of ML-based medical imaging remains unaddressed. This project will advance the state-of-the-art in ML fairness applied to the design of image-based computer-aided diagnosis systems.
Liste des tous les projets
WeNet, 2019-2023, H2020, Gatica-Perez
Smartphone sensing research involving university students in the Global South
AI4Media, 2020-2024, H2020, Gatica-Perez
Participatory approaches for human-centered AI understanding of local Swiss news
ICARUS, 2020-2024, H2020, Gatica-Perez
Design thinking approaches for urban security solutions in European cities
ELIAS, 2023-2027, Horizon Europe, Gatica-Perez
Machine learning for urban local development
SEM24, 2023-2025, Innosuisse, Van der Plas
Multilingual language technologies
IICT, 2022-2026, Innosuisse, Magimai Doss
Sign language and spoken subtitling technology to overcome language barriers
NCCR Evolang, 2020-2024, SNSF, Magimai Doss
Speech technologies for children speech
SMILE-II, 2021-2024, SNSF Sinergia, Magimai Doss
Technologies for Deaf/Hard of Hearing people
CollabCloud, 2022-2023, Loterie Romande & Idiap, Anjos
Collaborative research cloud Infrastructure powering discovery and exchange
FairMI, 2023-2026, SNSF, Anjos
Bias analysis and mitigation in image-based computer-aided diagnosis
SAFER, 2022-2024, Hasler, Marcel
Bias mitigation in facial recognition