• 🇧🇷 Professor of Computer Engineering at CEFET-MG (Divinópolis Campus)
• 🎓 PhD in Bioengineering
• 🔬 Researcher working on drug discovery, virtual screening, bioinformatics, and deep learning
• 🧠 Interested in artificial intelligence, computer vision, scientific computing, Linux, and reproducible workflows
• 💻 On GitHub, I share software projects, teaching materials, academic templates, and technical experiments
• 📫 Contact: tiagofga@gmail.com

My main research interests include:

• Deep learning for drug discovery and repositioning
• Virtual screening and molecular representation learning
• Bioinformatics and AI for scientific applications
• Computer vision and applied machine learning
• Scientific software, data pipelines, and reproducible computational workflows

• Structure-based virtual screening: from classical to artificial intelligence
  Frontiers in Chemistry, 2020

• Virtual Screening Algorithms in Drug Discovery: a review focused on machine and deep learning methods
  Drugs and Drug Candidates, 2023

• Evaluation of Docking Machine Learning and Molecular Dynamics Methodologies for DNA-Ligand Systems
  Pharmaceuticals, 2022

• 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

Here are some public repositories that reflect different parts of my work:

• mlp
  A C++ project for multilayer perceptrons, with CMake support, examples, tests, and optional OpenMP/CUDA backends.

• be-the-hero
  A full-stack learning project with backend, frontend, and mobile applications.

• Estruturas-de-Dados-em-C
  Educational repository with C implementations and teaching materials for data structures.

• ModeloPreProjetoPFC
  Template for undergraduate final project pre-proposals in Computer Engineering.

• Modelo-de-Apresentação-CEFET-MG
  Presentation template for final project defenses and academic use.

Core technologies

Data, ML & AI

Web

Mobile

Databases

DevOps & Cloud

I’m open to collaboration in areas such as:

• AI and deep learning for scientific applications
• Drug discovery, virtual screening, and bioinformatics
• Data engineering and reproducible computational workflows
• Educational software and teaching resources
• Research-oriented software projects and applied machine learning