Inês Domingues

inesdomingues@gmail.com

I am an Assistant Professor at the Faculty of Medicine of the University of Porto and a researcher at CI-IPOP and RISE-Health, working at the intersection of Artificial Intelligence, Data Science, Medical Imaging, and Health Decision Support Systems.

My academic background combines Applied Mathematics, Electrical and Telecommunications Engineering, and a PhD in Electrical and Computer Engineering, awarded with Cum Laude distinction. Before joining academia, I worked in the technology industry as Chief Technology Officer at Follow Inspiration and as Senior Software Developer at Vision-Box, where I developed computer vision, robotics, biometric recognition, and liveness detection solutions.

My research focuses on AI-driven biomedical and oncological image analysis, with applications in cancer diagnosis, prognosis, radiomics, medical imaging, and healthcare data science. I have authored more than 60 scientific publications, participated in several funded research projects, and served on more than 70 scientific committees.

Alongside research, I am strongly committed to teaching, supervision, and pedagogical innovation. I have taught courses in Artificial Intelligence, Machine Learning, Bioinformatics, Clinical Databases, and Intelligent Decision Systems, and have supervised or mentored students across BSc, MSc, PhD, and postdoctoral levels.

I also contribute actively to the scientific community through editorial roles, peer review, conference organisation, and professional associations, including APRP and IAPR.

Other Websites: LinkedIn profile, Google Scholar Citations; Semantic Scholar; DBLP; Research Gate profile; Scopus profile; ORCID 0000-0002-2334-7280; Web of Science; Quora; Academia; GitHub; Kudos; Authenticus; OpenReview; ScholarGPS; Mendeley. Identificador na plataforma CIÊNCIA ID 971F-F25B-1E79 (CiênciaVitae)

Guest Editor – MDPI Sensors

Special Issue: Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques (2nd Edition)
Submission Deadline: 29 September 2026
More Information

PhD students

2021-present: Bruno Mendes, "Radiomic Features for a Prostate Cancer Evaluation Framework", Doctoral Program in Biomedical Engineering, Faculty of Engineering, University of Porto
2022-2025: Ana Carolina Rodrigues, "Bi-parametric MRI Radiomics in the Spectrum of Prostate Cancer Treatment – Assessing the Trustworthiness of AI Models", HEADS - Programa Doutoral em Ciência de Dados de Saúde, Faculdade de Medicina da Universidade do Porto

Papers in the spotlight

Mendes, B., Domingues, I., Silva, A., & Santos, J. (2021). Prostate cancer aggressiveness prediction using CT images. Life, 11(11), 1164.
Amorim, J.P., Domingues, I, Abreu, P.H.; Santos, J. (2018). Interpreting Deep Learning Models for Ordinal Problems. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN).
Jasieniecka, A.; Domingues, I. (2025). CRISPR-Cas9 and Its Bioinformatics Tools: A Systematic Review. Current Issues in Molecular Biology, 47(5), 307.
Niño, S. B., Bernardino, J., & Domingues, I. (2024). Algorithms for liver segmentation in computed tomography scans: A historical perspective. Sensors, 24, 1752.
Domingues, I., Muller, H., Ortiz, A., Dasarathy, B. V., Abreu, P. H., & Calhoun, V. (2020). Guest Editorial: Information Fusion for Medical Data: Early, Late, and Deep Fusion Methods for Multimodal Data. IEEE Journal of Biomedical and Health Informatics, 24.

The complete list of my publications is available at Google Scholar Citations.