Positions | Education | Links | Interests | Publications | Supervision | Awards | Other Links
Gabriel Bianchin de Oliveira
Gabriel Bianchin de Oliveira is a Postdoctoral Fellow in Computer Science at Florida International University (FIU). He received his Ph.D. and M.Sc. in Computer Science from the University of Campinas (Unicamp), and his B.Sc. in Computer Science from the Federal Institute of Southern Minas Gerais (IFSULDEMINAS).
Positions
- Postdoctoral Fellow in Computer Science
Aug 2025 – Present
Education
- Ph.D. in Computer Science
Universidade Estadual de Campinas, Instituto de Computação
Advisor: Zanoni Dias
Co-Advisor: Hélio Pedrini
- M.Sc. in Computer Science
Universidade Estadual de Campinas, Instituto de Computação
Advisor: Zanoni Dias
Co-Advisor: Hélio Pedrini
- B.Sc. in Computer Science
Links
- gabriel.oliveira@ic.unicamp.br
- Curriculum Vitae
- Lattes
- ORCID
- Github
Interests
- Machine Learning
- Deep Learning
- Natural Language Processing
- Bioinformatics
Publications
- Journal Papers
- Ana Paula S. Dantas, Gabriel B. de Oliveira, Helio Pedrini, Cid C. de Souza and Zanoni Dias. Fair Age Prediction through ILP-Based Multi-Attribute Training Subset Selection. Applied Soft Computing. 2026.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. SUPERMAGOv2: Protein Function Prediction via Transformer Embeddings and Bitscore-Weighted Features. IEEE Access. 2025.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. SUPERMAGO: Protein Function Prediction based on Transformer Embeddings. PROTEINS: Structure, Function, and Bioinformatics. 2025.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. TEMPROT: protein function annotation using transformers embeddings and homology search. BMC Bioinformatics. 2023.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Ensemble of Template-Free and Template-Based Classifiers for Protein Secondary Structure Prediction. International Journal of Molecular Sciences. 2021.
- Internacional Conferences - Full Papers
- Wilson Bagni Junior, Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. A Comparative Study of Autoencoder Models on Latent Space Organization: An Evaluation with SVHN. 15th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2026). SciTePress.
- Yeonatan Mauhnoom, Gabriel Bianchin de Olivera, Helio Pedrini and Zanoni Dias. From Graphs to Images: Non-Parametric PPI Context Integration for Vision-Based Protein Function Prediction. 21st International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2026). SciTePress.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Scaling Up ESM2 Architectures for Long Protein Sequences Analysis: Long and Quantized Approaches. Brazilian Symposium on Bioinformatics 2024 (BSB’ 2024). pp 1-11. SBC.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Integrating Transformers and AutoML for Protein Function Prediction. 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2024). pp 1-5. IEEE.
- Ana Paula dos Santos Dantas, Gabriel Bianchin de Oliveira, Helio Pedrini, Cid Carvalho de Souza and Zanoni Dias. The Multi-Attribute Fairer Cover Problem. 12th Brazilian Conference on Intelligent Systems (BRACIS 2023). pp 163-177. Springer.
- Ana Paula dos Santos Dantas, Gabriel Bianchin de Oliveira, Daiane Mendes de Oliveira, Helio Pedrini, Cid Carvalho de Souza and Zanoni Dias. Algorithmic Fairness Applied to the Multi-Label Classification Problem. 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2023). pp 737-744. SciTePress.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Protein Molecular Function Annotation based on Transformer Embeddings. 11th Brazilian Conference on Intelligent Systems (BRACIS 2022). pp 210-220. Springer.
- Felipe Lopes Mello, Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Prediction of Protein Molecular Functions Using Transformers. 21st International Conference on Artificial Intelligence and Soft Computing (ICAISC 2022). 379-387. Springer.
- Thiago Dong Chen, Gabriel Bianchin de Oliveira and Zanoni Dias. Ensemble of Patches for COVID-19 X-ray Image Classification. 14th International Conference on Agents and Artificial Intelligence (ICAART 2022). pp 561-567. SciTePress.
- Gabriel Oliveira, Lucas David, Rafael Padilha, Ana Paula da Silva, Francine de Paula, Lucas Infante, Lucio Jorge, Patricia Xavier and Zanoni Dias. Bias Assessment in Medical Imaging Analysis: a Case Study on Retinal OCT Image Classification. 14th International Conference on Agents and Artificial Intelligence (ICAART 2022). pp 574-580. SciTePress.
- Daniel Ferber, Felipe Vieira, João Dalben, Mariana Ferraz, Nicholas Sato, Gabriel Oliveira, Rafael Padilha and Zanoni Dias. Deep Learning-based COVID-19 diagnostics of low-quality CT images. Brazilian Symposium on Bioinformatics 2021 (BSB’ 2021). pp 69-80. Springer.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. MMEC: Multi-Modal Ensemble Classi er for Protein Secondary Structure Prediction. 19th International Conference on Computer Analysis of Images and Patterns (CAIP 2021). pp 175-187. Springer.
- Gabriel Oliveira, Rafael Padilha, André Dorte, Luis Cereda, Luiz Miyazaki, Maurício Lopes and Zanoni Dias. COVID-19 X-ray Image Diagnostic with Deep Neural Networks. Brazilian Symposium on Bioinformatics 2020 (BSB’ 2020). pp 57-68. Springer.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Fusion of BLAST and Ensemble of Classifiers for Protein Secondary Structure Prediction. 33rd Conference on Graphics, Patterns and Images (SIBGRAPI 2020). pp 308-315. IEEE.
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Ensemble of Bidirectional Recurrent Networks and Random Forests for Protein Secondary Structure Prediction. 27th International Conference on Systems, Signals and Image Processing (IWSSIP 2020). pp 311-316. IEEE.
- Internacional Conferences - Short Papers
- Gabriel Bianchin de Oliveira, Helio Pedrini and Zanoni Dias. Protein Secondary Structure Prediction Based on Fusion of Machine Learning Classifiers. 36th Symposium on Applied Computing – Track Bioinformatics (ACM SAC BIO 2021). pp 26-29. ACM.
- Thesis
- Gabriel Bianchin de Oliveira. Anotações de Funções de Proteínas Utilizando Aprendizado de Máquina e Alinhamento Local. Doctoral’s Dissertation. 2025.
- Gabriel Bianchin de Oliveira. Predição de Estruturas Secundárias de Proteínas usando Aprendizado de Máquina e BLAST. Master’s Thesis. 2021.
- Gabriel Bianchin de Oliveira. Sistema de Predição de Proteínas Efetoras baseado na Análise Comparativa de Algoritmos de Classificação de Aprendizado de Máquina. Senior’s Thesis. 2018.
- Tecnical Reports
- Thiago Dong Chen, Gabriel Bianchin de Oliveira e Zanoni Dias. Diagnóstico de COVID-19 usando Redes Neurais Profundas. Projeto Final de Graduação (PFG). 2021.
- Felipe Lopes de Mello, Gabriel Bianchin de Oliveira e Zanoni Dias. Predição de Funções Moleculares de Proteínas utilizando Aprendizado de Máquina. Projeto Final de Graduação (PFG). 2021.
Supervision
- M.Sc. Students
- André Amadeu Satorres. Started in 2026.
- Yeonatan Mauhnoom. Preliminary title: Anotação de Funções Proteicas Utilizando Redes de Interações Proteína-Proteína. Co-advised with Zanoni Dias and Hélio Pedrini. Started in 2024.
Awards
- Best Master Thesis Award, Institute of Computing, University of Campinas (2021).
- Best Paper Award, XIII Brazilian Symposium on Bioinformatics (BSB), 2020.
Other Links
- SUPERMAGO+Web
An online web server for protein function prediction is available here, providing an accessible interface for researchers to analyze protein sequences.
- Location of Robots in Space Exploration
Project developed during the mobile robotics course. The paper is available here (in Portuguese).
- Analysis of Respiratory Clinical Conditions
Project developed during the e-Science course. The project is available here (in Portuguese).
- Semantic Segmentation on Targeted Spraying in the Farming
Project developed during the deep learning course. The paper is available here (in Portuguese).