Tiago Gonçalves

Porto, Portugal tiago.f.goncalves@inesctec.pt

PhD Student at FEUP | Research Assistant at INESC TEC | Machine Learning and Deep Learning Enthusiast

I received my MSc in Bioengineering (Biomedical Engineering) from Faculdade de Engenharia da Universidade do Porto (FEUP) in 2019. Currently, I am a PhD student in Electrical and Computer Engineering at FEUP and a research assistant at the Centre for Telecommunications and Multimedia of INESC TEC with the Visual Computing & Machine Intelligence (VCMI) Research Group.
My research interests include machine learning, explainable artificial intelligence (in-model approaches), computer vision, medical decision support systems, and machine learning deployment.

Besides working, I enjoy practising Karate-Do Shotokai or reading about life, philosophy, economy, politics or fundamental science.
Moreover, I do not refuse a good TV series or a good film (preferably at the cinema).

Experience

Invited Teaching Assistant

Faculdade de Ciências | Universidade of Porto

Invited Teaching Assistant during the 1st Semester of 2024-2025 on the course LBAW - Database and Web Applications Laboratory (L.EIC023)

Invited Teaching Assistant during the 2nd Semester of 2024-2025 on the course IA - Artificial Intelligence (L.EIC029)

September 2024 - July 2025

Visiting Researcher / PhD Student

Netherlands Cancer Institute

Visiting PhD student at the Department of Radiology, under the supervision of Wilson Silva

April 2024 - August 2024

Visiting Researcher / PhD Student

University of Utrecht

Visiting PhD student with AI Technology for Life research group of the Department of Information and Computing Sciences, under the supervision of Wilson Silva

April 2024 - August 2024

External Researcher / PhD Student

Athinoula A. Martinos Center for Biomedical Imaging | Massachusetts General Hospital

External PhD student with The Quantitative Translational Imaging in Medicine Lab (QTIM), under the supervision of Albert Kim and Christopher P. Bridge

February 2024 - Present

Visiting Researcher / PhD Student

Athinoula A. Martinos Center for Biomedical Imaging | Massachusetts General Hospital

Visiting PhD student with The Quantitative Translational Imaging in Medicine Lab (QTIM), under the supervision of Albert Kim and Christopher P. Bridge

September 2023 - February 2024

Invited Teaching Assistant

Faculdade de Engenharia | Universidade do Porto

Invited Teaching Assistant during the 1st Semester of 2022-2023 on the course PRO - Programming (L.EEC004)

September 2022 - February 2023

Invited Teaching Assistant

Faculdade de Engenharia | Universidade do Porto

Invited Teaching Assistant during the 1st Semester of 2021-2022 on the course TAIA - Advanced Topics on Artificial Intelligence (MECD14)

September 2021 - February 2022

Research Assistant

INESC TEC | Centre for Telecommunications and Multimedia

January 2020 - Present

Research Assistant

Faculdade de Engenharia | Universidade do Porto

September 2019 - December 2019

Junior Researcher

Fraunhofer Portugal AICOS

March 2018 - September 2018

Education

Faculdade de Engenharia | Universidade do Porto

Doctor of Philosophy (PhD)

Electrical and Computer Engineering

Thesis Title: ''Interpretable Machine Learning and its Application to Medical Decision Support Systems''

Scientific Supervisor: Jaime S. Cardoso

September 2020 - Present

Faculdade de Engenharia | Universidade do Porto

Bachelor of Science (BSc) & Master of Science (MSc)

Bioengineering - Biomedical Engineering

Thesis Title: ''Deep Aesthetic Assessment of Breast Cancer Surgery Outcomes''

Scientific Supervisor: Jaime S. Cardoso

Scientific Co-Supervisor: Wilson Silva

September 2016 - July 2019

University of Twente

Bachelor of Science (BSc)

Bioengineering - Biomedical Engineering

Internship and Bachelor's Thesis as an Erasmus+ Student

February 2016 - June 2016

Faculty of Biotechnology | Universidade Católica Portuguesa

Bachelor of Science (BSc)

Bioengineering - Biomedical Engineering

September 2013 - July 2016

Skills

Programming Languages & Tools

News & Awards

News

[2024/12/10] I gave a workshop about artificial intelligence applied to scientific research and ethics to the community of the Master in Sustainable Energies of Instituto Superior de Engenharia do Porto. Thank you for discussing science with me! You can get the slides here.
[2024/11/08] I talked about artificial intelligence for healthcare to the Service of Pediatric Surgery of the Centro Hospitalar Universitário de São João in Porto. Thank you for discussing science with me! You can get the slides here.
[2024/05/01] I presented my research on interpretable machine learning to the AI Technology for Life research group of the Department of Information and Computing Sciences of the Utrecht University. Thank you for discussing science with me! You can get the slides here.
[2023/10/27] I presented my research on interpretable machine learning to the AI for Multi-center Data research group of the Department of Radiology of the Netherlands Cancer Institute. Thank you, Wilson Silva (and colleagues), for inviting and listening to me! You can get the slides here.
[2023/10/26] INESC TEC's BIP Magazine highlighted two of my recent achievements! The first is the victory at the "Image CLEF Medical GANs" of the ImageCLEF Challenge 2023, alongside Helena Montenegro, Pedro Neto, Cristiano Patrício, Isabel Rio-Torto, Tiago Gonçalves and Luís F. Teixeira. The second is the victory at the Discover Datathon 2023, promoted by the Society of Critical Care Medicine (SCCM) alongside João Matos. Thank you!
[2023/05/31] The Centre of Telecommunications and Multimedia (CTM) coordinators recognised me as one of INESC TEC's "Incredibles" of May 2023. Thank you for this positive appreciation of my work, leading to this nomination. Last but not least, this nomination is only possible thanks to the incredible people with whom I have the privilege of interacting and collaborating: this nomination is also yours. Thank you!
[2023/03/18] I gave a talk titled "Interpretable Artificial Intelligence in Medicine: What Else?" for the XIV Symposium on Bioengineering. You can get the slides here. I want to thank Bioengineering Students Association from the Faculty of Engineering of the University of Porto / School of Medicine and Biomedical Sciences (NEB-FEUP/ICBAS) for the invitation!
[2023/03/15] I gave a talk titled "Attention Mechanisms for Medical Applications: Claims, Potentialities and Future Challenges" for Deep Learning Sessions Portugal. You can get the slides or watch the video. I want to thank Deep Learning Sessions Portugal for the invite and Startup Lisboa and Neuraspace for supporting the event!

Awards

MICCAI Hackathon 2021 Best Contribution Award - Member of the winning team "HIT" (Helena Montenegro, Isabel Rio-Torto, João Nunes and Tiago Gonçalves) with the work titled "Show Me Consistency! Increasing the quality and consistency of annotations"
2^nd Place World Data League - Member of the team "Tech Moguls" (Joana Morgado, Paulo Maia, Tiago Gonçalves and Tomé Albuquerque) that achieved 2^nd place at the World Data League competition on data science

Publications

Articles in International Journals and Conference Proceedings

Tiago Gonçalves, Anna Hedström, Aurélie Pahud de Mortanges, Xiaoxiao Li, Henning Müller, Jaime S. Cardoso, Mauricio Reyes, "Chapter 15 - Interpretable AI for medical image analysis: methods, evaluation, and clinical considerations", Editor(s): Marco Lorenzi, Maria A. Zuluaga, In The MICCAI Society book Series, Trustworthy AI in Medical Imaging, Academic Press, 2025, Pages 315-346, ISBN 9780443237614,
[link][bib][pdf]

Maria Miguel Beirão, João Matos, Tiago Gonçalves, Camila Kase, Luis Filipe Nakayama, Denise de Freitas, and Jaime S. Cardoso. "Classification of Keratitis from Eye Corneal Photographs using Deep Learning," 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal, 2024, pp. 3060-3065, doi: 10.1109/BIBM62325.2024.10821883.
[link][bib][pdf][presentation][code]

Margarida Vieira, Tiago Gonçalves, Wilson Silva and Ana F. Sequeira. "An End-to-End Framework to Classify and Generate Privacy-Preserving Explanations in Pornography Detection." 2024 International Conference of the Biometrics Special Interest Group (BIOSIG), Darmstadt, Germany, 2024, pp. 1-6
[link][bib][pdf][presentation][code]

Inês Martins, João Matos, Tiago Goncalves, Leo A. Celi, An-Kwok Ian Wong, Jaime S. Cardoso (2024). Evaluating the Impact of Pulse Oximetry Bias in Machine Learning under Counterfactual Thinking. In Proceedings of the Third Workshop on Applications of Medical Artificial Intelligence (AMAI) (in MICCAI 2024)
[link][bib][pdf][presentation][code]

Mohammad Hossein Zolfagharnasab, Nuno Freitas, Tiago Goncalves, Eduard Bonci, Carlos Mavioso, Maria J. Cardoso, Helder P. Oliveira, Jaime S. Cardoso (2024). "Predicting Aesthetic Outcomes in Breast Cancer Surgery: A Multimodal Retrieval Approach."" In Proceedings of the Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care (in MICCAI 2024)
[link][bib][pdf][poster][code]

Eduarda Caldeira, Pedro C. Neto, Tiago Gonçalves, Naser Damer, Ana F. Sequeira, and Jaime S. Cardoso. "Disentangling Morphed Identities for Face Morphing Detection." Science Talks 10 (2024): 100331.
[link][bib]

Isabel Rio-Torto, Tiago Gonçalves, Jaime S. Cardoso, and Luís F. Teixeira. "On the Suitability of B-cos Networks for the Medical Domain." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2024.
[link][bib][pdf][poster][code]

Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett, Katharina V. Hoebel, Mason Cleveland, Syed Rakin Ahmed, Elizabeth Gerstner et al. "Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology." arXiv preprint arXiv:2404.16397 (2024).
[link][bib][pdf][poster][presentation][code]

Pedro C. Neto, Rafael M. Mamede, Carolina Albuquerque, Tiago Gonçalves, and Ana F. Sequeira. "Massively Annotated Datasets for Assessment of Synthetic and Real Data in Face Recognition." arXiv preprint arXiv:2404.15234 (2024).
[link][bib][pdf]

Caldeira, Eduarda, Pedro C. Neto, Tiago Gonçalves, Naser Damer, Ana F. Sequeira, and Jaime S. Cardoso. "Unveiling the two-faced truth: Disentangling morphed identities for face morphing detection." In 2023 31st European Signal Processing Conference (EUSIPCO), pp. 955-959. IEEE, 2023.
[link][bib][pdf][code]

Kaidar-Person, Orit, Marilia Antunes, Jaime S. Cardoso, Oriana Ciani, Helena Cruz, Rosa Di Micco, Oreste D. Gentilini et al. "Evaluating the ability of an artificial-intelligence cloud-based platform designed to provide information prior to locoregional therapy for breast cancer in improving patient's satisfaction with therapy: The CINDERELLA trial." PLoS One 18, no. 8 (2023): e0289365.
[link][bib][pdf]

Pedro Serrano e Silva, Ricardo Cruz, A. S. M. Shihavuddin, and Tiago Gonçalves. "Interpretability-Guided Human Feedback During Neural Network Training." In Iberian Conference on Pattern Recognition and Image Analysis, pp. 276-287. Cham: Springer Nature Switzerland, 2023.
[link][bib][pdf][poster][code]

Diana Teixeira e Silva, Ricardo Cruz, Tiago Gonçalves, and Diogo Carneiro. "Two-stage semantic segmentation in neural networks." In Fifteenth International Conference on Machine Vision (ICMV 2022), vol. 12701, pp. 122-131. SPIE, 2023.
[link][bib][pdf][presentation][code]

Castro, Eduardo, Pedro M. Ferreira, Ana Rebelo, Isabel Rio-Torto, Leonardo Capozzi, Mafalda Falcão Ferreira, Tiago Gonçalves et al. "Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition." Machine vision and applications 34, no. 1 (2023): 16.
[link][bib][pdf]

Ricardo Cruz, Diana Teixeira E. Silva, Tiago Gonçalves, Diogo Carneiro, and Jaime S. Cardoso. "Two-Stage Framework for Faster Semantic Segmentation." Sensors 23, no. 6 (2023): 3092.
[link][bib][pdf][code]

Helena Montenegro, Pedro Neto, Cristiano Patrício, Isabel Rio-Torto, Tiago Gonçalves, and Luís F. Teixeira. "Evaluating Privacy on Synthetic Images Generated using GANs: Contributions of the VCMI Team to ImageCLEFmedical GANs 2023." Challenge (2023): 8.
[link][bib][pdf][code]

Isabel Rio-Torto, Cristiano Patrício, Helena Montenegro, Tiago Gonçalves, and Jaime S. Cardoso. "Detecting concepts and generating captions from medical images: Contributions of the VCMI team to Image-CLEFmedical caption 2023." In CLEF2023 Working Notes, CEUR Workshop Proceedings, CEUR-WS. org, Thessaloniki, Greece. 2023.
[link][bib][pdf][code]

Wilson Silva, Tiago Gonçalves, Kirsi Härmä, Erich Schröder, Verena Carola Obmann, María Cecilia Barroso, Alexander Poellinger, Mauricio Reyes, and Jaime S. Cardoso. "Computer-aided diagnosis through medical image retrieval in radiology." Scientific reports 12, no. 1 (2022): 20732.
[link][bib][pdf]

Marco Huber, Fadi Boutros, Anh Thi Luu, Kiran Raja, Raghavendra Ramachandra, Naser Damer, Pedro C. Neto et al. "SYN-MAD 2022: Competition on face morphing attack detection based on privacy-aware synthetic training data." In 2022 IEEE International Joint Conference on Biometrics (IJCB), pp. 1-10. IEEE, 2022.
[link][bib][pdf]

Pedro C. Neto, Tiago Gonçalves, Marco Huber, Naser Damer, Ana F. Sequeira, and Jaime S. Cardoso. "OrthoMAD: Morphing Attack Detection Through Orthogonal Identity Disentanglement." In 2022 International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1-5. IEEE, 2022.
[link][bib][pdf][code]

Tiago Gonçalves, Isabel Rio-Torto, Luís F. Teixeira, and Jaime S. Cardoso. "A Survey on Attention Mechanisms for Medical Applications: Are We Moving Toward Better Algorithms?." IEEE Access 10 (2022): 98909-98935.
[link][bib][pdf][code]

Pedro C. Neto, Tiago Gonçalves, João Ribeiro Pinto, Wilson Silva, Ana F. Sequeira, Arun Ross, and Jaime S. Cardoso. "Explainable biometrics in the age of deep learning." arXiv preprint arXiv:2208.09500 (2022).
[link][bib][pdf]

Isabel Rio-Torto, Cristiano Patrício, Helena Montenegro, and Tiago Gonçalves. "Detecting Concepts and Generating Captions from Medical Images: Contributions of the VCMI Team to ImageCLEFmedical 2022 Caption." (2022).
[link][bib][pdf][poster][presentation][code]

Paulo Maia, Joana Morgado, Tiago Gonçalves, and Tomé Albuquerque. "Applying Machine Learning for Traffic Forecasting in Porto, Portugal." In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 299-308. Cham: Springer International Publishing, 2021.
[link][bib][pdf]

Ana F. Sequeira, Tiago Gonçalves, Wilson Silva, João Ribeiro Pinto, and Jaime S. Cardoso. "An exploratory study of interpretability for face presentation attack detection." IET Biometrics 10, no. 4 (2021): 441-455.
[link][bib][pdf]

João Ribeiro Pinto Tiago Gonçalves, Carolina Pinto, Luís Sanhudo, Joaquim Fonseca, Filipe Gonçalves, Pedro Carvalho, and Jaime S. Cardoso. "Audiovisual classification of group emotion valence using activity recognition networks." In 2020 IEEE 4th International Conference on Image Processing, Applications and Systems (IPAS), pp. 114-119. IEEE, 2020.
[link][bib][pdf]

Tiago Gonçalves, Wilson Silva, Maria J. Cardoso, and Jaime S. Cardoso. "Deep image segmentation for breast keypoint detection." In Proceedings, vol. 54, no. 1, p. 35. MDPI, 2020.
[link][bib][pdf]

Sara P. Oliveira, João Ribeiro Pinto, Tiago Gonçalves, Rita Canas-Marques, Maria-João Cardoso, Hélder P. Oliveira, and Jaime S. Cardoso. "Weakly-supervised classification of HER2 expression in breast cancer haematoxylin and eosin stained slides." Applied Sciences 10, no. 14 (2020): 4728.
[link][bib][pdf][code]

Tiago Gonçalves, Wilson Silva, Maria J. Cardoso, and Jaime S. Cardoso. "A novel approach to keypoint detection for the aesthetic evaluation of breast cancer surgery outcomes." Health and Technology 10 (2020): 891-903.
[link][bib][pdf][code]

Ana F. Sequeira, Wilson Silva, Joao Ribeiro Pinto, Tiago Gonçalves, and Jaime S. Cardoso. "Interpretable biometrics: Should we rethink how presentation attack detection is evaluated?." In 2020 8th International Workshop on Biometrics and Forensics (IWBF), pp. 1-6. IEEE, 2020.
[link][bib][pdf]

Tiago Gonçalves, Wilson Silva, and Jaime Cardoso. "Deep aesthetic assessment of breast cancer surgery outcomes." In XV Mediterranean Conference on Medical and Biological Engineering and Computing-MEDICON 2019: Proceedings of MEDICON 2019, September 26-28, 2019, Coimbra, Portugal, pp. 1967-1983. Springer International Publishing, 2020.
[link][bib][pdf]

Abstracts in International Journals and Conference Proceedings

Timo Schinköthe, Eduard-Alexandru Bonci, Orit Kaidar-Person, Helena Cruz, Rosa Di Micco, Oreste Gentilini, Jörg Heil et al. "The CINDERELLA APProach: Future Concepts for Patient Empowerment in Breast Cancer Treatment with Artificial Intelligence-Driven Healthcare Platform." European Journal of Cancer 200 (2024).
[link][bib][pdf]

Eduard-Alexandru Bonci, Orit Kaidar-Person, Marilia Antunes, Oriana Ciani, Helena Cruz, Rosa Di Micco, Oreste Gentilini, Pedro Gouveia, Jörg Heil, Pawel Kabata and Nuno Freitas et al. 2024. "CINDERELLA Trial: validation of an artificial-intelligence cloud-based platform to improve the shared decision-making process and outcomes in breast cancer patients proposed for locoregional treatment." European Journal of Surgical Oncology, 50(2).
[link][bib][pdf]

André Pfob, Eduard-Alexandru Bonci, Orit Kaidar-Person, Marília Antunes, Oriana Ciani, Helena Cruz, Rosa Di Micco et al. "108TiP CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions." ESMO Open 9 (2024).
[link][bib]

Eduard-Alexandru Bonci, Orit Kaidar-Person, Marília Antunes, Oriana Ciani, Helena Cruz, Rosa Di Micco, Oreste Davide Gentilini et al. "Abstract PO3-19-11: CINDERELLA Clinical Trial (NCT05196269): using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions." Cancer Research 84, no. 9_Supplement (2024): PO3-19.
[link][bib]

Eduard-Alexandru Bonci, Orit Kaidar-Person, Marilia Antunes, Oriana Ciani, Helena Cruz, Rosa Di Micco, Oreste Davide Gentilini et al. "CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions." (2024): TPS621-TPS621.
[link][bib][pdf]

Shreyas Bhat Brahmavar, Tiago Goncalves, Tobias R. Bodenmann, Syed Rakin Ahmed, Jay B. Patel, Praveer Singh, Katharina V. Hoebel, Mason C. Cleveland, Felix Dorfner, Dagoberto Pulido-Arias, Philipp Hahnel, Jaime S. Cardoso, Jayashree Kalpathy-Cramer, Priscilla Brastianos, Elizabeth Gerstner, Albert E. Kim, Christopher P. Bridge (2024). "Deep Learning-based Non-Invasive Molecular Profiling of Brain Metastases from MR Imaging."
[link][bib][pdf][poster][code]

Inês Martins, João Matos, Tiago Goncalves, Leo Anthony Celi, A. Ian Wong, Jaime S. Cardoso (2024). "Thermometry Bias in Critical Care and Impact in Downstream Machine Learning Tasks."
[link][bib][poster]

Maria Beirão, João Matos, Tiago Goncalves, Camila Kase, Luis Filipe Nakayama, Jaime S. Cardoso (2024). "A machine learning system for keratitis diagnosis from cornea images."
[link][bib][poster]

Dagoberto Pulido Arias, Tiago Goncalves, Jayashree Kalpathy-Cramer, Elizabeth Gerstner, Jaime S. Cardoso, Albert Kim, Christopher P. Bridge (2024). "Dissecting the Impact of Data Augmentation on Whole Slide Image Classification."
[link][bib][presentation]

Articles in National Journals and Conference Proceedings

Tiago Gonçalves, Leonardo Capozzi, Ana Rebelo and Jaime S. Cardoso. "Deep Image Segmentation based on Mutual Information: A Study" 30th Portuguese Conference in Pattern Recognition (RECPAD), 2024.
[bib][pdf][poster][code]

Leonardo Capozzi, Tiago Gonçalves, Jaime S. Cardoso and Ana Rebelo. "Towards Fingerprint Presentation Attack Generation using Generative Adversarial Networks" 30th Portuguese Conference in Pattern Recognition (RECPAD), 2024.
[bib][pdf][poster][code]

Mohammad Hossein Zolfagharnasab, Nuno Freitas, Tiago Gonçalves, Eduard Bonci, Carlos Mavioso, Maria J. Cardoso, Hélder P. Oliveira and Jaime S. Cardoso. "Multimodal Deep Learning for Predicting Aesthetic Outcomes in Breast Cancer Surgery" 30th Portuguese Conference in Pattern Recognition (RECPAD), 2024.
[bib][pdf][poster][code]

Tiago Gonçalves, Leonardo Capozzi, Ana Rebelo and Jaime S. Cardoso. "Optimisation of Deep Neural Networks using a Genetic Algorithm: A Comparative Study" 29th Portuguese Conference in Pattern Recognition (RECPAD), 2023.
[bib][pdf][poster][code]

Leonardo Capozzi, Tiago Gonçalves, Jaime S. Cardoso and Ana Rebelo. "Analysis of Neurons' Information in Deep Spiking Neural Networks using Information Theory" 29th Portuguese Conference in Pattern Recognition (RECPAD), 2023.
[bib][pdf][poster][code]

Isabel Rio-Torto, Cristiano Patrício, Helena Montenegro, Tiago Gonçalves and Jaime S. Cardoso. "Detecting Concepts and Generating Captions from Medical Images" 29th Portuguese Conference in Pattern Recognition (RECPAD), 2023.
[bib][pdf][poster][presentation][code]

Helena Montenegro, Pedro Neto, Cristiano Patrício, Isabel Rio-Torto, Tiago Gonçalves and Luís F. Teixeira. "Evaluating Privacy on Synthetic Images Obtained using Deep Generative Models" 29th Portuguese Conference in Pattern Recognition (RECPAD), 2023.
[bib][pdf][poster][presentation][code]

Eduarda Caldeira, Eduardo Meca Castro and Tiago Gonçalves. "From Easy to Hard: A Curriculum Learning Approach for Breast Lesion Classification" 28th Portuguese Conference in Pattern Recognition (RECPAD), 2022.
[bib][pdf][poster][code]

Diana Teixeira e Silva, Ricardo Cruz and Tiago Gonçalves. "Preliminary Study on Deep Iterative Semantic Segmentation" 28th Portuguese Conference in Pattern Recognition (RECPAD), 2022.
[bib][pdf][poster][code]

Tiago Gonçalves and Jaime S. Cardoso. "Preliminary Study on the Impact of Attention Mechanisms for Medical Image Classification" 27th Portuguese Conference in Pattern Recognition (RECPAD), 2021.
[bib][pdf][poster][code]

Tiago Gonçalves, Wilson Silva and Jaime S. Cardoso. "A Deep Image Segmentation Approach to Breast Keypoint Detection" 26th Portuguese Conference in Pattern Recognition (RECPAD), 2020.
[bib][pdf][poster]

Sara P. Oliveira, João R. Pinto, Tiago Gonçalves, Hélder P. Oliveira and Jaime S. Cardoso. "IHC Classification in Breast Cancer H&E Slides with a Weakly-Supervised Approach" 26th Portuguese Conference in Pattern Recognition (RECPAD), 2020.
[bib][pdf][poster]

Wilson Silva, João R. Pinto, Tiago Gonçalves, Ana F. Sequeira and Jaime S. Cardoso. "Explainable Artificial Intelligence for Face Presentation Attack Detection" 26th Portuguese Conference in Pattern Recognition (RECPAD), 2020.
[bib][pdf][poster]

Tiago Gonçalves, Wilson Silva, and Jaime Cardoso. "Towards a Deep Keypoint Detection Algorithm for the Aesthetic Assessment of Breast Cancer Surgery Outcomes" 25th Portuguese Conference in Pattern Recognition (RECPAD), 2019.
[bib][pdf]

Rybarczyk, Yves, Clément Cointe, Tiago Gonçalves, Vitor Minhoto, Jan Kleine Deters, Santiago Villarreal, Arián Aladro Gonzalo, Jonathan Baldeón, and Danilo Esparza. "On the use of natural user interfaces in physical rehabilitation: A web-based application for patients with hip prosthesis." Journal of Science and Technology of the Arts 10, no. 2 (2018): 15-24.
[link][bib][pdf]

Dissertations and Theses

Tiago Filipe Sousa Gonçalves "Deep Aesthetic Assessment of Breast Cancer Surgery Outcomes"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto, 2019.
[link][bib]

Activity

Supervised MSc Students

Co-supervisor of Leonor Justo dos Santos Fernandes (2024-Present)
"Disentanglement and Assessment of Shortcuts on Ophthalmological Retinal Imaging Exams"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Mafalda Luisa Sampaio Oliveira (2023-2024)
"Bias detection and mitigation for Biometrics Explainable Artificial Intelligence methods applied to Face Recognition"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Carolina Mendes Catarino Cerveira Albuquerque (2023-2024)
"An integrated and user-friendly platform for the deployment of explainable Artificial Intelligence methods applied to Face Recognition"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Diogo de Almeida Campas (2023-2024)
"Deep Learning Generative Models for Breast MRI Synthesis: A 3D-GAN Comparative Study"
Master in Electrical and Computer Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of João Afonso Martins Domingues Andrade (2023-2024)
"Enhancing Lung CT 3D Image Synthesis with Generative Adversarial Networks"
Master in Informatics and Computing Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Pedro Manuel Santos Pereira (2023-2024)
"Deep Learning for Image Super-Resolution: Enhancing Generated CT Scans"
Master in Informatics and Computing Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Carlos Miguel de Sá Veloso (2023-2024)
"A Deep Segmentation Approach for the Retrieval of Breast Cancer Treatment Outcomes"
Master in Data Science and Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Maria Miguel Santos Beirão (2023-2024)
"Classification of Keratitis from Eye Corneal Photographs using Deep Learning: A Comparative Study on Amoeba, Bacteria, and Fungi"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Inês Alves Martins (2023-2024)
"A Data-Driven Framework for the Assessment and Mitigation of Clinical Measurement Disparities"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Margarida Jorge Cerqueira Vieira (2023-2024)
"Classifying and Explaining Pornography Detection: An End-to-End Framework"
Master in Informatics and Computing Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Pedro João Cruz Serrano e Silva (2021-2022)
"Human Feedback during Neural Networks Training"
Master in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of José Pedro Moreira de Almeida Baptista (2021-2022)
"Website Development for the VCMI Research Group"
Master in Informatics and Computing Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of João Gonçalves Rodrigues (2019-2020)
"WebBCCT.core - A Web Application for the Assessment of Breast Cancer Conservative Treatment Cosmetic Results"
Master in Network and Informatic Systems Engineering, Faculty of Sciences of the University of Porto

Supervised BSc Students

Co-supervisor of David Ferreira Sá Machado (2021-2022)
"Classification of Breast Masses using a Multiple-feature Regularisation Approach"
Bachelor in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Diana Raquel Teixeira e Silva (2021-2022)
"Semantic Segmentation in Neural Networks using Iterative Visual Attention"
Bachelor in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Érica Ferreira Gomes (2021-2022)
"Classification of Breast Lesion Features using a Concept-learning Algorithm"
Bachelor in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Manuel Leão Fortunato (2021-2022)
"Identification of Breast Cancer Features: A Classification Algorithm based on Concept Learning"
Bachelor in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Co-supervisor of Maria Eduarda Loureiro Caldeira (2021-2022)
"From Easy to Hard: a Curriculum Learning Approach for Breast Lesion Classification"
Bachelor in Bioengineering - Biomedical Engineering, Faculty of Engineering of the University of Porto

Supervised Internships

Co-supervisor of Ana Cristina da Silva Gomes (2022)
"Classify and Protect"
ANEEB Summer Internships 2022, Portuguese Biomedical Engineering Students' Association (ANEEB)

Co-supervisor of Margarida Duarte da Conceição (2022)
"Towards a unified framework to assess Deep Learning medical explanations"
ANEEB Summer Internships 2022, Portuguese Biomedical Engineering Students' Association (ANEEB)

Co-supervisor of Beatriz Arcipreste, Cláudia Ribeiro and José Macedo (2022)
"Classification of human activity in videos"
CTM Summer Internships 2022, Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)

Co-supervisor of André Soares (2021)
"xAI for COVID-19 Classification: Using explainable artificial intelligence to assess deep neural networks"
CTM Summer Internships 2021, Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)

Co-supervisor of Daniel Silva and Raquel Belo (2021)
"Interpretable Machine Learning for Mammography Screening"
NEB Outclass Internship, Faculty of Engineering of the University of Porto

Co-supervisor of João Abelha, João Ribeiro and José Matias (2020)
"WebBCCT.core - A Web Application for the Assessment of Breast Cancer Conservative Treatment Cosmetic Results"
CTM Summer Internships 2020, Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)