Foundational Insights from My Research
I engage in multifaceted investigations that encompass Federated Learning, Trustworthy AI, Affective Computing, HCI, Decentralized LLMs, normative frameworks, and the study of complex systems. Each strand of this work contributes to a holistic understanding of ethical AI applications, guiding the development of robust, privacy-preserving technologies.
12+
Peer-Reviewed Publications
3
Major Research Grants
5+
Active Collaborations
$0
Open Access
Delve into advanced methodologies
1000+
lines of specialized code
Hands-on development contributions with necessary augmentation to power the research projects that leverage Machine Learning in sensitive societal contexts.
Federated Learning
Exploring secure, decentralized approaches that preserve data ownership and enable robust model training across diverse institutions.
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Trustworthy AI
Ensuring algorithmic transparency, fairness, and reliability, guided by rigorous auditing and normative frameworks for responsible deployment.
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Affective Computing
Investigating emotion-driven interfaces, sensor analytics, and adaptive systems that support mental health monitoring and personalized interventions.
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Decentralized LLMs
Advancing locally deployed language models to reduce data transfers, strengthen privacy, and promote equitable research contributions worldwide.
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Exploring Ethical and Inclusive Technologies
Our open-source frameworks empower researchers and practitioners to adopt, customize, and extend advanced AI solutions without extensive coding expertise. By bridging theoretical insights and real-world applications, we enable transparent collaboration and scalable societal benefits.
Pioneering Approaches for Global Impact
Through decentralized architectures, we respect data sovereignty and uphold ethical guidelines. These cutting-edge methods offer a pathway to inclusive research that transcends geographical and organizational boundaries.
J’ai eu l’opportunité de suivre et d’accompagner Roy Saurabh dans ses travaux de recherche à l’Université Paris Cité, notamment dans le cadre de son doctorat, où il a exploré l’intersection entre les sciences cognitives, l’intelligence artificielle et la gouvernance des données personnelles.
En tant que membre de son comité technique, j’ai pu constater son engagement à développer des solutions innovantes pour la conformité réglementaire et la gouvernance des risques liés à l’IA. Son projet AffectLog s’inscrit dans cette dynamique en proposant une approche de fédération des données pour l’évaluation des risques liés à l’IA, alignée avec les principes de confidentialité et de transparence définis dans des cadres comme le RGPD et l’EU AI Act.
Grégoire Börst
Professeur de Psychologie du développement
Directeur du LaPsyDÉ
As Chief Operating Officer of JA Worldwide, I have had the opportunity to work directly with Dr. Roy Saurabh since 2021, when AffectLog became one of our innovation partners. JA Worldwide—one of the largest and most influential youth-serving NGOs globally—engaged AffectLog to enhance our efforts around responsible digital transformation and ethical AI integration within youth and education-focused ecosystems.
In recognition of his deep subject-matter expertise and his commitment to public-interest technology, we were pleased to appoint Roy to the Research Advisory Council of the JA Research Institute. This role underscores the trust we place in his interdisciplinary insights and strategic guidance on youth-centered innovation, ethics, and learning ecosystems.
Caroline Jenner
Chief Operating Officer, JA Worldwide
J’ai connu Roy Saurabh depuis son parcours en master, où nous avons collaboré sur des thématiques de recherche avancées en jumeaux numériques affectifs, affective computing et apprentissage socio-émotionnel basé sur l’IA éthique.
Son travail s’appuyait sur une analyse interdisciplinaire mêlant sciences cognitives, psychologie appliquée et intelligence artificielle. L’objectif était de développer des systèmes respectueux centrés sur l’analyse des cognitions et des émotions humaines tout en s’assurant de la confidentialité des données.
Franck Zenasni
Professeur de psychologie
Directeur adjoint de l’UMR LaPEA
Collaborate in Research
Connect with us to explore interdisciplinary projects at the intersection of AI risk assessment, federated learning, and policy, aiming to drive transformative solutions in healthcare, financial services, research data, skills and beyond.
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