Personal profile
Biographical details
I am a computer scientist and an engineer with a PhD in Neuroscience and Cognition from Universidade Federal do ABC (Brazil). Through my carrer, I realized how with the current explosion of technologies producing large scale measurements in neuroimaging applied to psychiatry and neurology it has became a field of research where one can develop interesting computational strategies and make discoveries. I have a long-time interest in machine learning methods (especially Deep Learning) and neuroimaging, focusing mainly on leveraging the power of next-generation tools. Before joining the lab, I was working in Brazil as a Assistant Professor where I was developing my teaching skills.
External positions
Assistant Professor, Univ Fed ABC, Universidade Federal do ABC (UFABC), Ctr Math Computat & Cognit
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
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Collaborations and top research areas from the last five years
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Neurofind: Using deep learning to make individualised inferences in brain-based disorders
Vieira, S., Baecker, L., Lopez Pinaya, W., Garcia Dias, R., Scarpazza, C., Calhoun, V. & Mechelli, A., 27 Feb 2025, (E-pub ahead of print) In: Translational psychiatry. 15, 1, 69.Research output: Contribution to journal › Article › peer-review
Open AccessFile88 Downloads (Pure) -
Synthesis of Annotated Data for Medical Image Segmentation: (a Chapter of "Generative Machine Learning Models in Medical Image Computing")
Fernandez, V., Borges, P., Graham, M., Lopez Pinaya, W. H., Vercauteren, T. & Cardoso, J., 2025, Generative Machine Learning Models in Medical Image Computing: Synthesis of Annotated Data for Medical Image Segmentation. Springer, p. 3-24 21 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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A 3D Generative Model of Pathological Multi-modal MR Images and Segmentations
Fernandez, V., Pinaya, W. H. L., Borges, P., Graham, M. S., Vercauteren, T. & Cardoso, M. J., 2024, Deep Generative Models - Third MICCAI Workshop, DGM4MICCAI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Mukhopadhyay, A., Oksuz, I., Engelhardt, S., Zhu, D. & Yuan, Y. (eds.). Springer Science and Business Media Deutschland GmbH, p. 132-142 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14533 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
4 Citations (Scopus) -
Generating multi-pathological and multi-modal images and labels for brain MRI
Fernandez, V., Pinaya, W. H. L., Borges, P., Graham, M. S., Tudosiu, P.-D., Vercauteren, T. & Cardoso, M. J., Oct 2024, In: Medical Image Analysis. 97, 21 p., 103278.Research output: Contribution to journal › Article › peer-review
Open AccessFile8 Citations (Scopus)9 Downloads (Pure) -
Geometry-Invariant Abnormality Detection
Patel, A., Tudosiu, P. D., Pinaya, W. H. L., Adeleke, O., Cook, G., Goh, V., Ourselin, S. & Cardoso, M. J., 2023, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings. Greenspan, H., Greenspan, H., Madabhushi, A., Mousavi, P., Salcudean, S., Duncan, J., Syeda-Mahmood, T. & Taylor, R. (eds.). Springer Science and Business Media Deutschland GmbH, p. 300-309 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14220 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
1 Citation (Scopus)