Projects | Professional website of Sébastien Marcel

DEMO-AI

Wed, 01 Apr 2026 00:00:00 +0000

Access to factual information is essential for democratic decision-making, public trust, and civic engagement, yet artificial intelligence (AI) enables large-scale creation and dissemination of manipulated content, fabricated narratives, and content amplification that can distort public perception, erode confidence in democratic institutions, and polarize political discourse. These risks threaten to reshape political debates, influence electoral outcomes, and undermine public trust in media sources in Switzerland. Democratic values can be upheld by developing AI tools and governance frameworks to counter disinformation and monitor media framing.

DEMO-AI is an interdisciplinary research project, driving advances in computing to enhance the resilience of democracy, integrating expertise from law, journalism and communication studies, media and information literacy to ensure that AI-supported solutions align with democratic values and regulations. Four project goals include:

AI tools for analyzing news media framing;
AI tools for detecting manipulation of audio-visual media;
legal research on regulatory frameworks for AI and disinformation in Switzerland;
and engaging both the public and professionals in evaluating and testing media tools.

DEMO-AI will produce tools to analyze issue framing and related narratives in Swiss media, facilitate the detection of audio-visual disinformation, and understand legal challenges. These tools will be designed, tested, and refined in collaboration with the general public and professionals, placing their specific needs at the center, thus ensuring real-world applicability. Through societal impact activities, the project extends beyond technology, addressing key challenges across AI, democracy, and policy.

INTERART

Wed, 01 Apr 2026 00:00:00 +0000

The INTERART project brings together the Geneva’s Museum of art and history (MAH), the University of Oxford, the Idiap Research Institute, as well as the School of criminal justice of the University of Lausanne. Together, these institutions are collaborating to uncover the identities of subjects in the MAH’s historical portrait collection, many of whom remain unknown. Notably, the project investigates suspected portraits of Marie-Antoinette, Queen of France, and Marie-Caroline, Queen of Naples, by Jean-Étienne Liotard.

Heterogeneous face recognition is being used to uncover the identities of the sitters. This technology enables a face recognition system to compare faces in diverse media (coloured image, thermal image, drawing, painting). It opens new paths for interpretation and could enable us to reveal the identities of the individuals portrayed.

The project perfectly aligns with Idiap’s vision, demonstrating how artificial intelligence can serve society by unveiling new insights and enriching the disciplines it engages with. It also underscores the wide-ranging applications of AI and the Institute’s cutting-edge expertise.

Supported by the Loterie Romande, the project includes several phases, with an exhibition at the MAH in autumn 2026 and a publication.

CERTAIN

Wed, 01 Jan 2025 00:00:00 +0000

CERTAIN focuses on the ethical and regulatory transparency of AI systems, with the goal of helping organizations assess and improve compliance in a practical and technically grounded way.

The project delivers guidelines and tools to support regulatory compliance, assess data quality, measure bias in datasets, and protect privacy. It aligns closely with broader work on trustworthy biometrics and responsible AI by combining technical evaluation with legal, ethical, and operational considerations.

ROSALIND

Thu, 01 Feb 2024 00:00:00 +0000

ROSALIND focuses on defending digital identity systems against malicious AI-generated face images and manipulated identity documents.

The project combines two complementary goals: developing robust anti-fraud defenses for document images and selfie-videos, and using generative AI to improve the robustness and balance of authentication algorithms. It sits at the intersection of biometric security, digital identity, and applied trustworthy AI.

ROSALIND is a strong example of translational biometrics research with direct relevance to real-world identity verification.

CARMEN

Mon, 01 Jan 2024 00:00:00 +0000

CARMEN develops biometric solutions for non-stop border control for both pedestrians and vehicles in uncontrolled environments.

The project addresses the practical difficulties of “on-the-move” biometrics, including lower-quality live data, lack of time to read ePassports, and real operational constraints outside controlled indoor checkpoints. It aims to make biometric border technologies more accurate, reliable, and deployable in realistic large-scale scenarios.

PopEye

Mon, 01 Jan 2024 00:00:00 +0000

PopEye develops robust privacy-preserving biometric technologies for passenger identification and verification at EU external borders.

The project addresses operational constraints such as open-air conditions, night-time acquisition, time pressure, and large-scale throughput, while emphasizing privacy-preserving design. Its goal is to improve the accuracy, reliability, and usability of biometric recognition in demanding border-management scenarios.

PopEye represents a current strand of work where biometric performance, privacy, and deployment realism must all be addressed together.

SAFER

Tue, 01 Mar 2022 00:00:00 +0000

SAFER addresses fairness and ethics in face recognition.

The project investigates how to assess and reduce unfair performance differences across demographic groups, with work spanning both training-time and scoring-time strategies. It also explores the role of synthetic and diverse datasets in improving the responsible development of face recognition systems.

SAFER reflects a broader commitment to trustworthy biometrics by combining technical performance with fairness, transparency, and responsible deployment.

BATL

Sun, 01 Jan 2017 00:00:00 +0000

BATL contributed to biometric anti-spoofing research in the context of the IARPA ODIN program, which aimed to strengthen biometric systems against known and unknown presentation attacks.

Within this line of work, research focused on robust face presentation-attack detection, anomaly detection, multi-channel sensing, and the creation of challenging datasets and protocols for evaluating spoof resilience. At Idiap, this effort is closely associated with work on multi-channel face anti-spoofing and datasets such as HQ-WMCA, supporting reproducible research on secure biometric acquisition.

BEAT

Thu, 01 Mar 2012 00:00:00 +0000

BEAT (Biometrics Evaluation and Testing) was a European FP7 project focused on creating an open and reproducible framework for the evaluation of biometric technologies.

The project addressed three complementary goals: transparent benchmarking of biometric systems, vulnerability analysis, and support for standardized evaluation procedures. It contributed to reproducible research practices in biometrics and helped establish evaluation workflows that were both rigorous and operationally relevant.

This project also supported the broader vision of open platforms and tools for the community, connecting research, benchmarking, and technology assessment.

TABULA RASA

Fri, 01 Jan 2010 00:00:00 +0000

TABULA RASA was a major European research project dedicated to understanding and mitigating spoofing attacks against biometric systems.

The project investigated the vulnerability of biometric modalities such as face and fingerprint to direct attacks and developed methods to detect and counter such threats. It played an important role in shaping the modern field of presentation-attack detection and helped establish anti-spoofing as a core topic in trustworthy biometrics.

This project remains a key milestone in the evolution of biometric security research and in the translation of anti-spoofing knowledge to practical evaluation settings.

MOBIO

Tue, 01 Jan 2008 00:00:00 +0000

MOBIO focused on mobile biometrics under realistic usage conditions, combining face and voice for authentication in noisy and unconstrained environments.

The project investigated robust face localisation, speech segmentation, video-based face authentication, speaker authentication, multimodal fusion, and unsupervised model adaptation over time. It also contributed a widely used multimodal database collected across multiple countries and sites, helping establish strong evaluation benchmarks for mobile biometric research.