Trustworthy AI for Post-Stroke Care

Lopes de Souza, Victor F.

doi:10.24963/ijcai.2026/945

Trustworthy AI for Post-Stroke Care

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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 8333-8334.

https://doi.org/10.24963/ijcai.2026/945

Keywords

AI Ethics, Trust, Fairnes: Explainability and interpretability
AI Ethics, Trust, Fairnes: Trustworthy AI
Humans and AI: Applications
Uncertainty in AI: Uncertainty representations

Abstract

As AI systems are increasingly deployed in high-stakes settings, two concerns become particularly important: cautiousness (awareness of model limitations for risk-aware decisions) and explainability (providing human-understandable justifications). My PhD research develops methods that enable both, from theoretical and application perspectives. On the theoretical side, I formalize cautious and interpretable models for multiple uncertainty frameworks, with algorithms for explanation and preference elicitation under uncertainty. On the application side, I implement these methods in post-stroke rehabilitation, designing AI systems that analyze multimodal clinical data to support individualized rehabilitation planning.

Victor F. Lopes de Souza. 2026. Trustworthy AI for Post-Stroke Care. In Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26. IJCAI, 8333–8334. https://doi.org/10.24963/ijcai.2026/945

@inproceedings{ijcai2026p945,
  title     = {Trustworthy AI for Post-Stroke Care},
  author    = {Lopes de Souza, Victor F.},
  booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
               Artificial Intelligence, {IJCAI-26}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Diego Calvanese},
  pages     = {8333--8334},
  year      = {2026},
  month     = {8},
  note      = {Doctoral Consortium},
  doi       = {10.24963/ijcai.2026/945},
  url       = {https://doi.org/10.24963/ijcai.2026/945},
}

TY  - CPAPER
TI  - Trustworthy AI for Post-Stroke Care
AU  - Lopes de Souza, Victor F.
T2  - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2026
SP  - 8333
EP  - 8334
DO  - 10.24963/ijcai.2026/945
UR  - https://doi.org/10.24963/ijcai.2026/945
ER  -