← Research Themes

Failure, Uncertainty & Embodied Explainability

Treats failure and uncertainty as inherent features of real-world human–robot and human-AI interaction rather than exceptional cases. Behavioural sensing and embodied cues — such as gaze, timing, motion, and affective expression — enable early detection of breakdowns and support timely explanation and recovery. These mechanisms are complemented by AI risk and uncertainty communication strategies that make system confidence, limitations, and intent legible to users.

People

Wafa Johal
Wafa Johal
Associate Professor
Ramtin Tabatabaei
Ramtin Tabatabaei
PhD Student
Sarah Schombs
Sarah Schombs
PhD Student

Publications

All Publications →
  1. One Body, Many Minds: Exploring Design Frictions and Considerations for Multi-Agentic Systems in Human-Robot Interaction
    Schömbs, Sarah, Zhang, Yan, Wang, Canghai, and Johal, Wafa
    In Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems Apr 2026
    Bib PDF 
    @inproceedings{schombs2026onebody,
  bibtex_show = {true},
  author = {Schömbs, Sarah and Zhang, Yan and Wang, Canghai and Johal, Wafa},
  title = {One Body, Many Minds: Exploring Design Frictions and Considerations for Multi-Agentic Systems in Human-Robot Interaction},
  booktitle = {Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems},
  series = {CHI EA '26},
  year = {2026},
  month = apr,
  address = {Barcelona, Spain},
  doi = {10.1145/3772363.3799366},
  isbn = {979-8-4007-2281-3/2026/04},
  pdf = {https://chri-lab.github.io/files/papers/2026_One_Body_Many_Minds_Exploring_Design_Frictions_and_Considerations_for_Multi-Agentic_Systems_in_Human-Robot_Interaction_Schombs.pdf},
  publisher = {ACM},
  research_theme = {failure-uncertainty}
}