R&D Team

Bridge the gap between academia and industry

The R&D team is dedicated to supporting and advancing the institute's missions (research, education, technology transfer) by developing, maintaining, and optimizing software tools, platforms, and infrastructure. Our goal is to enable researchers to focus on scientific innovation by providing robust, efficient, and user-friendly technical solutions.

Our work spans the full lifecycle of a research idea: building web and desktop applications, data acquisition systems, and robotic control software; maintaining reliable infrastructure and open-source releases; and documenting the tools researchers rely on daily. Beyond development, the team teaches and mentors — through onboarding, academic courses, and public outreach — and regularly contributes to research itself, co-authoring papers alongside colleagues across the institute.

We bridge this gap through four types of engagement:

  • Industrial projects: We turn research results into solutions that meet the requirements of industry partners.
  • Academic projects: We build prototypes and contribute directly to academic research work.
  • Internal support: We help with everyday development needs and maintain the team's software.
  • Software distribution: We manage the release process for both open-source software and industrial products.

Team

18
People
9+
Years at Idiap avg.

Over the last 5 years

90+
Projects
700+
Person months on projects

Latest publications

The EMN country factsheets structured dataset
Alonso del Barrio David, Gatica-Perez Daniel
Proceedings of the 35th ACM international conference on information and knowledge management
2026
Exploratory analysis of yellow mongoose vocalization: detection from in-the-wild recordings and call classification
Hovsepyan Sevada, Ben Mahmoud Imen, Rüegg Vanessa, Manser Marta, Magimai-Doss Mathew
Proceedings of interspeech
2026
Skill extraction from resumes and job offers across six languages
Vásquez-Rodrı́guez Laura, Audrin Bertrand, Michel Samuel, Galli Samuele, Rogenhofer Julneth, Negro Cusa Jacopo, Plas Lonneke
Proceedings of the 11th edition of the swiss text analytics conference
2026
Évaluation de la reconnaissance automatique de la parole par les grands modèles de langage génératifs
Bañeras-Roux Thibault, Kumar Shashi, Khalil Driss, Motlicek Petr, Burdisso Sergio, Liu Shiran, Rouvier Mickael, Wottawa Jane, Dufour Richard
EvalLLM2026 : Atelier sur l'évaluation des modèles génératifs (LLM), le RAG et challenges
2026