Isel Grau Garcia
Source: https://www.tue.nl/en/research/researchers/isel-grau-garcia Parent: https://www.tue.nl/en/news-and-events/news-overview/12-11-2025-super-powered-ai-from-eindhoven-helps-doctors-identify-cancer-and-other-diseases-more-quickly
Assistant Professor
Isel Grau Garcia
Contact
Department / Institute
Industrial Engineering and Innovation Sciences
Group
EAISI Foundational
EAISI Health
RESEARCH PROFILE
Isel Grau is an Assistant Professor in the Information Systems group at Eindhoven University of Technology (TU/e). Her research focuses on advancing Artificial Intelligence, particularly in recurrent neural networks, time-series analysis, data-driven decision-making, and explainable AI. A key aspect of her work is enhancing the interpretability of machine learning models by developing novel explanation methods and incorporating expert feedback to refine AI systems. She also enjoys interdisciplinary research, applying her expertise to diverse domains such as bioinformatics, materials science, healthcare, and supply chain forecasting to drive real-world impact.\ \ PhD SUPERVISION\ Isel Grau is promotor / co-promotor of:
- Mohsen Abbaspour Onari
- Gregor Baer
- Bram Biemans
My research transforms AI from black-box models into transparent decision-making tools that empower people to make informed and reliable choices.
ACADEMIC BACKGROUND
Isel Grau received her Ph.D. in Computer Science from Vrije Universiteit Brussel (VUB), Belgium, where her research focused on machine learning interpretability and semi-supervised classification. During her postdoctoral work at the Artificial Intelligence Laboratory of VUB, she collaborated on interdisciplinary projects funded by INNOVIRIS Brussels and IRP-VUB.
Isel has co-authored over 80 publications in peer-reviewed international conferences and journals and has been actively involved in organizing thematic workshops. She frequently serves as a reviewer for leading AI conferences and journals. She has also been a visiting researcher at institutions such as Warsaw University of Technology and the University of Lisbon.
Recent Publications
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[### Sparseness-optimized feature importance with prior knowledge and reinforcement learning-powered optimization
Neurocomputing
(2026)
Gonzalo Nápoles,Isel Grau,Yamisleydi Salgueiro](https://research.tue.nl/nl/publications/14c0e1db-142d-46a0-94c4-35200d42e09e) - [### Sparseness-Optimized Feature Importance for Time Series Classification
IEEE Access
(2026)
Isel Grau,Gonzalo Nápoles,Agnieszka Jastrzebska,Yamisleydi Salgueiro](https://research.tue.nl/nl/publications/09862356-db9b-4ccd-b6cf-a105fec26ed0) - [### A Review on Fuzzy Cognitive Mapping
Big Data and Cognitive Computing
(2026)
Gonzalo Nápoles,Agnieszka Jastrzebska,Isel Grau,Yamisleydi Salgueiro,Maikel Leon](https://research.tue.nl/nl/publications/d3eea28f-f4ff-4617-b16c-b084fbe0356b) - [### Inversion of the impedance response towards physical parameter extraction using interpretable machine learning
(2025)
Mahmoud Nabil,Isel Grau,Ricardo Grau-Crespo,Said Hamad,Juan A. Anta](https://research.tue.nl/nl/publications/c5d27410-c89e-40e7-af3c-49635abec7b6) - [### Class-Dependent Perturbation Effects in Evaluating Time Series Attributions
3rd World Conference on eXplainable Artificial Intelligence, XAI-2025
(2025)
Gregor Baer,Isel Grau,Chao Zhang,Pieter Van Gorp](https://research.tue.nl/nl/publications/1bda1f93-2cba-460d-b730-4c49071abe0a)
Ancillary Activities
No ancillary activities