Marc Fraile Fabrega
PhD student at Department of Information Technology; Vi3; Human Machine Interaction
- E-mail:
- marc.fraile.fabrega@it.uu.se
- Visiting address:
- Hus 10, Regementsvägen 10
- Postal address:
- Box 337
751 05 UPPSALA
Short presentation
Marc Fraile is a Ph.D. candidate under the Centre for Interdisciplinary Mathematics (CIM) at Uppsala University. He conducts his research in Uppsala Social Robotics Lab, in close collaboration with the Methods for Image Data Analysis (MIDA) group. His interests lie in developing explainable AI (XAI) methods, and applying those to make more trustable machines.
Personal webpage: https://marcfraile.github.io/
Keywords
- machine learning
- social robotics
- explainable-ai

Publications
Selection of publications
Part of Companion Publication of the 2021 International Conference on Multimodal Interaction, p. 403-407, 2021
- DOI for Automatic Analysis of Infant Engagement during Play: An End-to-end Learning and Explainable AI Pilot Experiment
- Download full text (pdf) of Automatic Analysis of Infant Engagement during Play: An End-to-end Learning and Explainable AI Pilot Experiment
Recent publications
UpStory: the uppsala storytelling dataset
Part of Frontiers in Robotics and AI, 2025
- DOI for UpStory: the uppsala storytelling dataset
- Download full text (pdf) of UpStory: the uppsala storytelling dataset
Are We Friends?: End-to-End Prediction of Child Rapport in Guided Play
Part of Computer Vision – ECCV 2024 Workshops, p. 380-392, 2024
Computer Vision and Explainability in Human-Human and Human-Robot Interaction
2024
A case study in designing trustworthy interactions: implications for socially assistive robotics
Part of Frontiers in Computer Science, 2023
- DOI for A case study in designing trustworthy interactions: implications for socially assistive robotics
- Download full text (pdf) of A case study in designing trustworthy interactions: implications for socially assistive robotics
Part of ICMI '22, p. 444-454, 2022
- DOI for End-to-End Learning and Analysis of Infant Engagement During Guided Play: Prediction and Explainability
- Download full text (pdf) of End-to-End Learning and Analysis of Infant Engagement During Guided Play: Prediction and Explainability
All publications
Articles in journal
UpStory: the uppsala storytelling dataset
Part of Frontiers in Robotics and AI, 2025
- DOI for UpStory: the uppsala storytelling dataset
- Download full text (pdf) of UpStory: the uppsala storytelling dataset
A case study in designing trustworthy interactions: implications for socially assistive robotics
Part of Frontiers in Computer Science, 2023
- DOI for A case study in designing trustworthy interactions: implications for socially assistive robotics
- Download full text (pdf) of A case study in designing trustworthy interactions: implications for socially assistive robotics
Comprehensive doctoral thesis
Conference papers
Are We Friends?: End-to-End Prediction of Child Rapport in Guided Play
Part of Computer Vision – ECCV 2024 Workshops, p. 380-392, 2024
Part of ICMI '22, p. 444-454, 2022
- DOI for End-to-End Learning and Analysis of Infant Engagement During Guided Play: Prediction and Explainability
- Download full text (pdf) of End-to-End Learning and Analysis of Infant Engagement During Guided Play: Prediction and Explainability
Part of Companion Publication of the 2021 International Conference on Multimodal Interaction, p. 403-407, 2021
- DOI for Automatic Analysis of Infant Engagement during Play: An End-to-end Learning and Explainable AI Pilot Experiment
- Download full text (pdf) of Automatic Analysis of Infant Engagement during Play: An End-to-end Learning and Explainable AI Pilot Experiment