AI for Everyone
To support individuals and communities outside mainstream Western societies, governments, NGOs, and businesses often use tools that were not designed with these users in mind. This needs to change.
Artificial intelligence should serve everyone, equitably. To achieve this, people—especially those whose voices are often not heard—need to be at the center of the design and deployment of AI systems. Through the development of participatory, trustworthy, and fair technology, research at Idiap empowers communities of users and fosters democratic, collective decision-making. The impact of our work is broad, ranging from citizen science initiatives to projects where the responsible use of AI can truly benefit communities.
Expertise domains
#Bioinformatics&HealthInformatics
#DataScience&SocialComputing
#HumanComputerInteraction
#Imaging&ComputerVision
#MachineLearning
#NaturalLanguageProcessing
#Robotics&AutonomousSystems
#Security&Privacy
#SignalProcessing
#Speech&AudioProcessing
This program contributes to the following UN SDG
More... Achieve gender equality and empower all women and girls.
More... Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels.
More...
People
ABBET, Philip
(Senior Research and Development Engineer)
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AKSTINAITE, Vita
(Postdoctoral Researcher)
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ALONSO DEL BARRIO, David
(Junior R&D / Research Assistant)
AMIRI, Mahdi
(PhD Student / Research Assistant)
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ANNAPUREDDY, Ravinithesh Reddy
(PhD Student / Research Assistant)
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ARMANI RENZO, Matheus
(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
(PhD Student / Research Assistant)
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BURDISSO, Sergio (Gastón)
(R&D / Research Assistant)
CANÉVET, Olivier
(Senior Research and Development Engineer)
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CAROFILIS VASCO, Roberto Andrés
(Postdoctoral Researcher)
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CARRON, Daniel
(Research and Development Engineer)
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CHEN, Haolin
(PhD Student / Research Assistant)
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CLIVAZ, Guillaume
(Senior Research and Development Engineer)
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COLBOIS, Laurent
(PhD Student / Research Assistant)
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COMAN, Andrei (Catalin)
(PhD Student / Research Assistant)
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COPPIETERS DE GIBSON, Louise
(PhD Student / Research Assistant)
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COSTA BARBOSA, Lucas
(Research Intern)
DAYER, Yannick
(Research and Development Engineer)
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DROZ, William
(Senior Research and Development Engineer)
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ECABERT, Christophe
(Postdoctoral Researcher)
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EL HAJAL, Karl
(PhD Student / Research Assistant)
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EL ZEIN, Dina
(PhD Student / Research Assistant)
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FEHR, Fabio (James)
(PhD Student / Research Assistant)
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GAIST, Samuel
(Senior Research and Development Engineer)
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GARNER, Philip
(Senior Research Scientist)
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GATICA-PEREZ, Daniel
(Senior Research Scientist with Academic Title)
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GENTILHOMME, Théophile
(Senior Research and Development Engineer)
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GEORGE, Anjith
(Research Associate)
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HE, Mutian
(PhD Student / Research Assistant)
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HENDERSON, James (Brinton)
(Senior Research Scientist)
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HERMANN, Enno
(Postdoctoral Researcher)
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HOU, Mingchi
(PhD Student / Research Assistant)
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HOVSEPYAN, Sevada
(Research Associate)
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ISMAYILZADA, Mahammad
(PhD Student / Research Assistant)
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JIMÉNEZ DEL TORO, Oscar (Alfonso)
(Postdoctoral Researcher)
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JUNG, Vincent
(PhD Student / Research Assistant)
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KALAAJI, Dana
(Research Intern)
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KALOGA, Yacouba
(Postdoctoral Researcher)
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KAYAL, Salim
(Senior Research and Development Engineer)
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KHALIL, Driss
(Junior R&D / Research Assistant)
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KODRASI, Ina
(Research Scientist)
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KOMATY, Alain
(Research Associate)
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KOPP, Damian
(Research Intern)
KORSHUNOV, Pavel
(Research Associate)
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KOTWAL, Ketan
(Research Associate)
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KRIVOKUĆA HAHN, Vedrana
(Research Associate)
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KULKARNI, Ajinkya (Vijay)
(Postdoctoral Researcher)
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KUMAR, Shashi
(PhD Student / Research Assistant)
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LUÉVANO GARCÍA, Luis Santiago
(Postdoctoral Researcher)
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MACEIRAS, Jérémy
(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)
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MAYORAZ, André
(Research and Development Engineer)
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MENENDEZ RUIZ DE AZUA, Pablo
(Research Intern)
MICHEL, Samuel
(Research and Development Engineer)
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MOHAMMADI, Amir
(Research Associate)
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MOTLICEK, Petr
(Senior Research Scientist)
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MURALIDHAR, Skanda
(Research Associate)
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NANCHEN, Alexandre
(Senior Research and Development Engineer)
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NEUGBER, Samuel
(R&D / Research Assistant)
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OTROSHI SHAHREZA, Hatef
(Postdoctoral Researcher)
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ÖZBULAK, Gökhan
(PhD Student / Research Assistant)
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PALLANCA, Olivier
(Visitor)
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PANNATIER, Yvan
(Research Intern)
PETERSEN, Molly (Rose)
(PhD Student / Research Assistant)
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POLAC, Magdalena
(R&D / Research Assistant)
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PRASAD, Amrutha
(PhD Student / Research Assistant)
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PULVIRENTI, Roberto
(Research Intern)
PUROHIT, Tilak
(PhD Student / Research Assistant)
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QUEIROZ NETO, Dilermando
(Visitor)
RABELLO DOS ANJOS, André
(Research Scientist)
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RAHIMI NOSHANAGH, Parsa
(PhD Student / Research Assistant)
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RAMIREZ CONTRERAS, Hector Manuel
(Research Intern)
RANGAPPA, Pradeep
(Postdoctoral Researcher)
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SANCHEZ LARA, Alejandra
(Research Intern)
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SANCHEZ-CORTES, Dairazalia
(Research Assistant)
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SARKAR, Eklavya
(PhD Student / Research Assistant)
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SHEIKH, Shakeel Ahmad
(Postdoctoral Researcher)
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SHIRAKAMI, Haruki
(PhD Student / Research Assistant)
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SYLA, Valmir
(Research Intern)
TARIGOPULA, Neha
(PhD Student / Research Assistant)
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THORBECKE (NIGMATULINA), Iuliia
(PhD Student / Research Assistant)
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TORNAY, Sandrine
(Postdoctoral Researcher)
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ULUCAN, Ibrahim
(Research Assistant)
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VAN DER MEER, Michiel
(Postdoctoral Researcher)
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VAN DER PLAS, Lonneke
(External Research Fellow)
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VÁSQUEZ RODRÍGUEZ, Laura
(Postdoctoral Researcher)
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VERZAT, Colombine
(Research and Development Engineer)
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VIDIT, Vidit
(Postdoctoral Researcher)
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VILLATORO TELLO, Esaú
(Research Associate)
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VLASENKO, Bogdan
(Research Associate)
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WEN, Jing
(Research Intern)
XI, Lei
(Research Intern)
ZANGGER, Alicia
(Research and Development Engineer)
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ZHANG, Alice (Chi)
(Visitor)
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Publication highlights
Generalization and Personalization of Passive Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries. Meegahapola, W. Droz, P. Kun, A. de Gotzen, C. Nutakki, S. Diwakar, S. Ruiz Correa, D. Song, H. Xu, M. Bidoglia, 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 Technologies (PACM IMWUT), 6(4), pp. 1-32, Dec. 2022.
A multidisciplinary approach with a large international team to quantify the performance of inference models for real-life smartphone sensor data, investigating country-specific, country-agnostic, and multi-country approaches. This work is an example of progress towards the development of diversity- aware algorithms for people in eight countries in Europe, Latin America, and Asia.
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.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, Sandrine Tornay, Skanda Muralidhar, Mathew Magimai-Doss, ACM International Conference on Multimodal Interaction, 2022.
Recently, a phonology-based sign language assessment approach has been proposed using sign language production acquired in 3D space using Kinect sensor. In order to scale the sign language assessment system to realistic application, there is need to reduce the dependency on Kinect, which is not accessible to wider community, and develop solutions that can potentially work with web-cameras. This paper takes a step in that direction by investigating sign language recognition and sign language assessment in 2D space either by dropping the depth coordinate in Kinect or using methods for skeleton estimation from videos. Experimental studies on Swiss German Sign Language corpus SMILE show that, while loss of depth information leads to considerable drop in sign language recognition performance, high level of sign language assessment performance can still be obtained.
Project highlights
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.
Full list of related projects
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