Inês Domingues
inesdomingues@gmail.com
Inês Domingues graduated in Applied Mathematics in the School of Sciences at the University of Porto in 2004, completed a Masters degree in Electrical and Telecommunications Engineering at Aveiro University in 2008, and finished the PhD in Electrical and Computer Engineering in the School of Engineering at the University of Porto in 2015 (Cum Laude).
She is currently an Assistant Professor (Professor Adjunto) at DEIS-ISEC and Researcher at Centro de Investigação do Instituto Português de Oncologia do Porto (CI-IPOP).
She teaches across the domain of Artificial Intelligence and is President part of the jury for accreditation of competences in the Informatics Engineering degrees (LEI, LEI-PL, and LEI-CE).
She is also the former president of APRP (Associação Portuguesa de Reconhecimento de Padrões) and Associate Editor of IEEE Access and Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization.
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; dblp. Identificador na plataforma CIÊNCIA ID 971F-F25B-1E79
Highlighted events
Special Session #3 at ICMASC'24: Advances in Computational Techniques for Medical Diagnostics and Treatment
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-present: 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
News
[2024 Apr] I was invited to be an IMIP session chair for the "Digital Medical Image Analysis and Processing Technology" session.
[2024, Mar] I was invited to joint the technical Program Committee of the 27th European Conference on Artificial Intelligence (ECAI)
[2024, Mar] Entry on Algorithms for Liver Segmentation in Computed Tomography Scans in Encyclopedia
[2024, Mar] I was invited to joint the technical Program Committee of the 1st International Conference on Explainable AI for Neural and Symbolic Methods” - EXPLAINS
[2024, Mar] Stephanie Batista Niño had her paper "Algorithms for Liver Segmentation in Computed Tomography Scans: A Historical Perspective" accepted at Sensors Special Issue on Biomedical Sensing and Bioinformatics Processing
[2024, Feb] I was invited to joint the technical Program Committee of the International Joint Conference on Biometrics
[2024, Feb] Stephanie Batista Niño had her paper "Algorithms for Liver Segmentation in Computed Tomography Scans: A Historical Perspective" available at PrePrints
[2024, Feb] I am a Program Committee Member of the 2024 International Workshop on Biometrics and Forensics (IWBF)
[2024, Jan] I am a Program Committee Member of the 2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON) - Special Session 18
[2024, Jan] Cátia Roriz finished her MSc project entitled "Enhancing Breast Cancer Diagnosis: A Mammogram Retrieval System and Ground Truth Application" at Instituto Superior de Engenharia de Coimbra (ISEC)
[2024, Jan] I am a Program Committee Member of the International Conference on Intelligent Medicine and Image Processing (IMIP)
[2023, Dec] I was invited to joint the technical Program Committee of the IEEE International Conference on Computer Vision and Machine Intelligence (IEEE CVMI)
[2023, Dec] Ana Carolina Rodrigues had her paper "Development and Prospective Validation of a Fully Automatic Bi-Parametric MRI Radiomics Signature to Predict Prostate Cancer Disease Aggressiveness: A Multi-Centric Study Using Over 4000 Patients" available at The Lancet PrePrints
[2023, Set] José Maurício had his paper "Distinguishing between Crohn's disease and Ulcerative colitis using Deep Learning Models with Interpretability" accepted at Pattern Analysis and Applications
[2023, Nov] I am a Program Committee Member of 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[2023, Set] José Maurício had his paper "Knowledge Distillation of Vision Transformers and Convolutional Networks to Predict Inflammatory Bowel Disease" accepted at 26th Iberoamerican Congress on Pattern Recognition (CIARP)
[2023, May] I have been awarded the Outstanding Associate Editor of 2022 for IEEE Access
[2023, Apr] José Maurício had his paper "Deep Neural Networks to distinguish between Crohn’s disease and Ulcerative colitis" accepted at 11th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)
[2023, Apr] José Maurício had his paper "Comparing Vision Transformers and Convolutional Neural Networks for Image Classification: A Literature Review" accepted at Applied Sciences
[2023, Apr] Ana Carolina Rodrigues had her paper "Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for Prediction of Prostate Cancer Disease Aggressiveness" accepted at Scientific Reports
Papers in the spotlight
Domingues, I., & Cardoso, J. S. (2014, August). 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). IEEE.
Martins, P., Domingues, I., Silva, A., & António, J. S. T. (2007). An MRI study of european portuguese nasals. In INTERSPEECH
Marques, F., Duarte, H., Santos, J., Domingues, I., Amorim, J. P., & Abreu, P. H. (2019, April). An iterative oversampling approach for ordinal classification. In Proceedings of the 34th ACM/SIGAPP symposium on applied computing (pp. 771-774).
Rodrigues, A., Rodrigues, N., Santinha, J., Lisitskaya, M. V., Uysal, A., Matos, C., ... & Papanikolaou, N. (2023). Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness. Scientific Reports, 13(1), 6206.
Cardoso, J. S., Sousa, R., & Domingues, I. (2012, December). 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.
