Advancing Affective Digital Twins with Scientific Rigor

Driven by Impact

Meet the advisors

Get to know the research pioneers informing AffectLog research approach.

Sarah Goodday

University of Oxford

Sarah’s expertise in epidemiological methods and mental health surveillance provided critical insights into data integrity and cross-institutional collaborations.

Vladimír Šucha

European University Institute

Vladimír Šucha expertise spans multiple sectors, with focus on evidence informed policymaking, innovation ecosystems, impacts of artificial intelligence (AI), on society.

Catherine Pelachaud

Sorbonne Université

Catherine Pelachaud is a French computer scientist specializing in human–computer interaction and known for her work virtual assistants and on generating facial expressions.

Andrey Kormilitzin

University of Oxford

Andrey’s expertise in mathematics, statistical machine learning and deep learning to address challenges involved in learning, inference and ethical decision making using complex biomedical and health data.

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Scientific Foundations of AffectLog Persona

AffectLog Persona advances the field of Affective Digital Twins (ADTs) by integrating multimodal emotion recognition, physiological signal processing, and computational models of affect regulation. By leveraging federated learning, Persona ensures that no raw data is centralized—only encrypted model updates are shared, preserving privacy while enabling robust affective insights.

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Our Advisory Board

Our scientific board consists of experts in affective computing, ethical AI, and decentralized learning, guiding AffectLog’s development toward privacy-first, evidence-based solutions that ensure autonomy, security, and regulatory compliance.

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A Culture of Scientific Excellence

AffectLog is committed to rigorous, reproducible AI research at the intersection of digital twins, human behavior modeling, and federated intelligence. By developing scientifically validated, ethically aligned affective AI models, we enable precise, privacy-preserving insights into real-time human affect and cognition.

Driven by Impact

Research Networks & Global Collaborations

AffectLog works with leading academic and industry partners to establish the future of Affective Digital Twins. We develop and test our models in interdisciplinary settings, ensuring empirical validation, ethical compliance, and scientifically grounded AI applications.

Affective Computing Consortium

Scientific AI Collaborators

Specialists in emotion modeling, physiological computing, and user-centric AI evaluation ensure scientific rigor and interdisciplinary integration.

Federated AI Research Group

Privacy-Preserving Intelligence

This research team develops cutting-edge federated learning protocols, homomorphic encryption, and zero-trust architectures for privacy-first affective AI.

Cognitive Neuroscience & AI Ethics

Regulatory & Human-Centric AI

Dedicated to ensuring transparent, ethical, and scientifically validated AI, this group integrates affective science into real-world digital twin applications.

Policy & Compliance Research

Global AI Governance

Focused on aligning federated AI development with regulatory requirements, this group shapes the scientific and legal frameworks governing affective digital twins.

Advantages

Why collaborate with us at AffectLog

AffectLog combines rigorous affective computing research, interdisciplinary collaboration, and privacy-enhancing AI architectures. Our platform enables secure, privacy-preserving emotion modeling in a scalable, scientifically validated frameworks, by enabling privacy-enhancing AI-driven affective state tracking.

Start your journey

Take the next step in developing scientifically rigorous, privacy-secure affective AI models with AffectLog.

Begin leveraging AffectLog’s Persona™ today!