Inês Domingues

I graduated from the School of Sciences at the University of Porto in 2004, majoring in Applied Mathematics. Later, I completed a Masters degree in Electrical and Telecommunications Engineering at Aveiro University in 2008. In 2015, I achieved my PhD in Electrical and Computer Engineering from the University of Porto, with Cum Laude distinction.

Currently, I am an Assistant Professor (Professor Adjunto) at DEIS-ISEC and a Researcher at both the Centro de Investigação do Instituto Português de Oncologia do Porto (CI-IPOP) and RISE-Health: Rede de Investigação em Saúde.

At DEIS-ISEC, I contribute to the domain of Artificial Intelligence by teaching various courses and serving as the president of the commission for accreditation of competences in Informatics Engineering degrees. My Teaching Personnel Performance Assessment Process for 2022 achieved an overall Qualitative Rating of Excellent.

 To complement my academic roles, I have served as the President of APRP (Associação Portuguesa de Reconhecimento de Padrões) and hold the position of Associate Editor for IEEE Access, where I received the Outstanding Associate Editor Award in 2020, 2022, 2023 and 2024. I am also an Associate Editor for Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualisation.

Throughout my career, I have gained extensive experience in research projects and technological development. I have worked as a Principal Investigator and Postdoctoral researcher in various projects funded by organisations such as IPO Porto, Norte Portugal Regional Operational Programme, and the Portuguese Agency for Innovation. 

My research primarily focuses on oncological prognosis, and breast and prostate cancer screening and diagnosis driven by image processing, pattern recognition and machine learning.

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: 20 February 2026
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• Special Issue:  Pattern Recognition Applications in Medical Image Analysis
  Submission Deadline: 25 February 2026
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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

• 2025-present: José Maurício, "Deep Learning for Improved Detection of Subtle Patterns", Programa Doutoral em Ciência de Computadores (PDCC), Faculdade de Ciências da Universidade do 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

News

• [2025, Jul] Ana Carolina Vitorino Rodrigues finished her PhD in Health Data Science (FMUP)

• [2025, May] Pedro Morais had his paper "Deep Learning Techniques for Detecting Morphed Face Images: A Literature Review" accepted at IEEE Access 

• [2025, May] I have been awarded the Outstanding Associate Editor of 2024 for IEEE Access

• [2025, May] Stephanie Batista had her paper "Private Data Incrementalization: Data-Centric Model Development for Clinical Liver Segmentation" accepted at Bioengineering 

• [2025, Apr] Alicja Jasieniecka had her paper "CRISPR-Cas9 and its Bioinformatic tools: a systematic review" accepted at Current Issues in Molecular Biology 

• [2025, Feb] Irena Wadas had her paper "Systematic Review of Phylogenetic Analysis Techniques for RNA Viruses Using Bioinformatics" accepted at the International Journal of Molecular Sciences 

• [2024, Dec] I was invited to join the technical Program Committee of the International Conference on Education Technology and Computers (ICETC 2025)

• [2024, Dec] I was invited to serve as Program Committee for the International Symposium on Biomechatronics and Robotics in Healthcare (BioMRH 2025)

• [2024, Dec] I was invited to serve as Meta Reviewer (TPC) for ISBI 2025 (2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI))

• [2024, Nov] I am a Program Committee Member of International Conference on Pattern Analysis and Machine Intelligence (ICPAMI 2025)   

• [2024, Nov] Stephanie Batista finished her MSc project entitled "2D Liver Segmentation in Abdominal Computed Tomography Scans" at Instituto Superior de Engenharia de Coimbra (ISEC)

• [2024, Aug] I am a Program Committee Member of the International Conference on Intelligent Medicine and Image Processing (IMIP) 2025  

• [2024, Jul] I was invited to join the Organizing Committee Member of the Global Annual Meet on Biomedical Engineering and Computational Biology (GAMBECB2025) 

• [2024, Jul] Bruno Mendes had his paper "Radiomic Pipelines for Prostate Cancer in External Beam Radiation Therapy: A Review of Methods and Future Directions" accepted at Journal of Clinical Medicine Section on Nephrology & Urology

Papers in the spotlight

• Amorim, J., Domingues, I., Abreu, P. H. & Santos, J. (2018) "Interpreting deep learning models for ordinal problems." European Symposium on Artificial Neural Networks (ESANN).

• Domingues, I., & Cardoso, J. S. (2014). Using Bayesian surprise to detect calcifications in mammogram images. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 1091-1094).

• Marques, F., Duarte, H., Santos, J., Domingues, I., Amorim, J. P., & Abreu, P. H. (2019). An iterative oversampling approach for ordinal classification. In Proceedings of the 34th ACM/SIGAPP symposium on applied computing (pp. 771-774). 

• Martins, P., Domingues, I., Silva, A., & António, J. S. T. (2007). An MRI study of european portuguese nasals. In INTERSPEECH

• Cardoso, J. S., Sousa, R., & Domingues, I. (2012). Ordinal data classification using kernel discriminant analysis: A comparison of three approaches. In 2012 11th International Conference on Machine Learning and Applications (Vol. 1, pp. 473-477). IEEE. 

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