Dr. Téo Sanchez

Personal information

Téo Sanchez is a postdoc specializing in human-AI interaction. He earned his Ph.D. in June 2022 as a member of the ExSitu research team at Université Paris-Saclay, under the supervision of Wendy E. Mackay and Baptiste Caramiaux.

He is now a Marie Skłodowska-Curie research fellow at the Munich Interactive Intelligence Initiative (MI3) at LMU Munich, mentored by Prof. Ophelia Deroy.

Research interests

His research focuses on designing and evaluating human interactions with machine learning systems—spanning data, processes, and models—with the goal of empowering non-ML experts to build and review AI systems effectively.

His current project explores the relationship between agency and understanding of ML models. By emphasizing self-directed, hands-on engagement with AI systems, rather than relying on traditional explanatory approaches, he aims to uncover how experiential interactions can enhance users’ understanding in these technologies.

As a secondary thread of research, he investigates the communities of practice that emerge around AI technologies in the creative and cultural industries. His work spans from studying the trail-blazing artists who began incorporating AI into their practices in the late 2010s to analysing recent online communities centered on recreational text-to-image generation.

Current projects

• Human teaching and auditing: Investigating how humans behave when teaching or testing a learning algorithm
• Evaluation methods of ML understanding and literacy: systematic literature review on evaluation methods of ML understanding and literacy.
• Marcelle: an open source toolkit for programming interactive machine learning applications.
• Artists using ML: Analysing the evolution of early artists who incorporated machine learning into their creative practices before 2020.

Selected publications

1. Sanchez, T., Caramiaux, B., Françoise, J., Bevilacqua, F., & Mackay, W. E. (2021). How do people train a machine? Strategies and (Mis) Understandings. Proceedings of the ACM on Human-Computer Interaction 5 (CSCW1), 1-26.
2. Françoise, J., Caramiaux, B., & Sanchez, T. (2021, October). Marcelle: composing interactive machine learning workflows and interfaces. In: The 34th Annual ACM Symposium on User Interface Software and Technology, 39-53.
3. Sanchez, T., Caramiaux, B., Thiel, P., & Mackay, W. E. (2022, March). Deep learning uncertainty in machine teaching. In: Proceedings of the 27th International Conference on Intelligent User Interfaces, 173-190.
4. Sanchez, T. (2023, June). Examining the Text-to-Image Community of Practice: Why and How do People Prompt Generative AIs?. In: Proceedings of the 15th Conference on Creativity and Cognition, 43-61.
5. Sungeelee, V., Sanchez, T., Jarrassé, N., & Caramiaux, B. (2024, March). Comparing Teaching Strategies of a Machine Learning-based Prosthetic Arm. In: Proceedings of the 29th International Conference on Intelligent User Interfaces, 715-730.