I am a Computer Engineering professor at CEFET-MG, a researcher in AI for drug discovery, and a software developer who enjoys turning scientific ideas into reproducible computational tools.
- 🔬 I research deep learning, virtual screening, molecular representations, and bioinformatics.
- 🎓 I hold a PhD in Bioengineering.
- 👨🏫 I create structured teaching resources for artificial intelligence, programming, algorithms, and data structures.
- 🧪 I build scientific software, data pipelines, and machine-learning experiments.
- 🌱 I am currently exploring better ways to make AI-assisted research reproducible and accessible.
- 🤝 I welcome collaborations at the intersection of artificial intelligence, science, and education.
My work focuses on machine- and deep-learning methods for drug discovery and repositioning, with particular interest in virtual screening, molecular representation learning, and reliable computational workflows.
| Project | What you will find |
|---|---|
| EC-IA | A public teaching hub for Artificial Intelligence at CEFET-MG, with guided studies, conceptual pseudocode, activities, and interactive search-algorithm visualizations. |
| mlp | A C++ multilayer perceptron implementation with CMake, examples, tests, and optional OpenMP/CUDA backends. |
| Estruturas-de-Dados-e-Algoritmos-em-C | C implementations and educational material for learning algorithms and data structures. |
| ModeloPreProjetoPFC | A reusable template for Computer Engineering undergraduate project proposals. |
| Modelo-de-Apresentação-CEFET-MG | An academic presentation template for final project defenses. |
- Structure-based virtual screening: from classical to artificial intelligence — Frontiers in Chemistry, 2020
- Evaluation of Docking Machine Learning and Molecular Dynamics Methodologies for DNA-Ligand Systems — Pharmaceuticals, 2022
- Virtual Screening Algorithms in Drug Discovery: a review focused on machine and deep learning methods — Drugs and Drug Candidates, 2023
- Drug Discovery by Deep Learning and Virtual Screening: Review and Case Study — Bioinformatics and Computational Biology, 2023
- Predição de classes farmacológicas para o descobrimento e reposicionamento de fármacos por redes neurais convolucionais — PhD thesis, 2025
More tools and platforms
|
|
|
Open to research collaborations, scientific software projects, and educational initiatives.