Digital Einstein
An embodied conversational AI agent bringing Albert Einstein back to life through multimodal interaction — combining speech synthesis, facial animation, and cognitive reasoning. …
I am a Senior Researcher & Lecturer at the Computer Graphics Laboratory of ETH Zurich, and a Research Consultant at Disney Research. I lead the Digital Character AI team at CGL and, as PI of an SNF Ambizione grant, a line of generative models that produce expressive 3D facial animation from speech and text under explicit control of emotion and expression. My research interests include conversational digital characters, generative animation, affective computing, human-computer interaction, and applied machine learning.
My vision is to create intelligent digital humans that can naturally communicate, understand, and support people across domains such as education and mental health. My research focuses on multimodal artificial intelligence for interactive digital humans, developing models that combine large language models, affective computing, and data-driven animation to create embodied conversational agents endowed with autonomous agency, consistent values, and beliefs.
My work bridges machine learning, human–computer interaction, and computer graphics to enable AI systems such as Digital Einstein and interactive patient avatars for psychotherapy training and health education.
Dr. sc. (PhD) in Computer Science
ETH Zurich
Master's Degree in Computer Science
ETH Zurich
Bachelor's Degree in Computer Science
ETH Zurich
My research addresses a fundamental challenge at the intersection of deep learning and human-centric AI: how can we build machine learning systems that not only perform with high accuracy but also meaningfully understand, adapt to, and collaborate with humans?
I work across three interconnected areas: multimodal deep learning for affective and behavioral understanding, leveraging smartphone sensors, egocentric vision, and physiological signals; agentic AI and cognitive architectures for conversational agents, enabling consistent personality, beliefs, and emotional states; and scalable generative models for embodied expression, developing efficient transformer pipelines for text-driven and speech-driven facial animation.
A flagship application is Digital Einstein, an embodied conversational agent that has reached thousands of visitors globally at events including SIGGRAPH, GITEX Global, and the World Economic Forum. My system also powers collaborative applied research in digital health — including a Virtual Psychotherapist for mental health support and RehaBot for patient health education.
Please reach out to collaborate.
An embodied conversational AI agent bringing Albert Einstein back to life through multimodal interaction — combining speech synthesis, facial animation, and cognitive reasoning. …
Multimodal deep learning systems for affective state prediction from smartphone sensors, biometric data, egocentric vision, and physiological signals — enabling real-world …
Deep learning-based cognitive frameworks that enable conversational agents to maintain consistent personality, beliefs, values, and emotional states across extended interactions — …
Efficient transformer-based pipelines for text-driven and speech-driven 3D facial animation — achieving real-time performance through phoneme-level speech modeling and contrastive …
Multimodal dialog act classification for conversations with digital characters — interpreting the communicative intent of user utterances to drive appropriate agent responses in …
Embodied conversational agents for mental health support, developed in partnership with Prof. Andrew Gloster (University of Lucerne). The project comprises a patient-facing …
An embodied AI avatar representing a medical professional, capable of conducting patient interactions, health assessments, and health education in rehabilitation and home-care …
A mobile AI platform for early detection of cognitive impairment in aging populations, integrating Large Geospatial Models for movement analysis, LLMs for conversational cognitive …
| Course | Role | Institution | Years |
|---|---|---|---|
| Artificial Intelligence for Digital Characters | Course creator & lecturer | ETH Zurich | 2024 – present |
| Seminar on Digital Humans | Course creator & lecturer | ETH Zurich | 2022 – present |
| Visual Computing | Head teaching assistant | ETH Zurich, D-INFK | 2022 – 2024 |
| Parallel Programming | Head teaching assistant | ETH Zurich, D-INFK | 2021 – 2023 |
| Informatik I | Teaching assistant | ETH Zurich, D-BAUG and D-MAVT | 2017 – 2021 |
An AI-driven simulated patient system for ACT psychotherapy training, combining clinically grounded virtual patients with real-time turn-by-turn ACT fidelity feedback. Expert …
A transformer pipeline for text-driven facial animation exploiting phoneme-level speech structure, achieving real-time performance and best-in-class lip synchronization accuracy. …
A new multimodal dataset and architecture combining egocentric vision and physiological signals for in-the-wild emotion and personality recognition, presented at NeurIPS 2025 …
BEE is a modular cognitive framework for conversational agents featuring belief management, value alignment, transparent reasoning, and extensibility. Best Paper Honorable Mention …
A full-pipeline platform for interactive AI character experiences, demonstrated through Digital Einstein and deployed at scientific conferences, technology events, and public …
EmoSpaceTime decouples emotion and content in 3D speech animation through contrastive learning, enabling fine-grained control over emotional expressivity independent of spoken …
A large-scale empirical characterization of the personality dimensions GPT-3 expresses during human-chatbot interaction, using Big Five psychometrics. Published in ACM IMWUT 2024.
Multimodal affective state prediction from smartphone touch and sensor data in naturalistic conditions, using deep learning fusion. CHI 2022.