Resume

Education

• Ph.D. in Computer Science, Federal University of Pernambuco (UFPE), 2025
  • Research area: Machine Learning
  • Thesis: Unsupervised Feature Selection and Deep Subspace Clustering for Exploratory High-Dimensional Cluster Analysis
• M.Sc. in Computer Science, Federal University of Pernambuco (UFPE), 2018
  • Research area: Machine Learning
  • Thesis: Unsupervised Feature Selection Methodology for Clustering in High-Dimensional Datasets
• Specialization in Software Engineering, University of Pernambuco (UPE), 2016
  • Focus: Service-Oriented Architecture (SOA)
• B.Sc. in Computer Science, Faculdade dos Guararapes, 2014

Work experience

• Feb 2026 – Present: Invited Assistant Professor
  • University of Coimbra, Coimbra, Portugal
  • Teaching and academic activities in Computer Science
  • Interactive Computer Graphics, Vulkan SDK, and high-performance rendering
  • Laboratory instruction, assessment, educational material development, and student support
• Jan 2026 – Present: Researcher
  • University of Coimbra – CISUC, Coimbra, Portugal
  • Research on unsupervised machine learning, Topological Data Analysis (TDA), knowledge graphs, and intelligent decision-support systems
  • Development of clustering and representation learning methods for structured and high-dimensional data
  • Research mentoring and collaboration with PhD students
• Apr 2025 – Aug 2026: Postdoctoral Researcher
  • University of Coimbra – CISUC, Coimbra, Portugal
  • E2E Digital Twin project for high-end natural cork stopper inspection
  • Research on computer vision, self-supervised learning, deep clustering, synthetic data generation, and explainable AI
  • Development of human-centered AI and Digital Twin solutions for industrial quality inspection
• Jul 2023 – Aug 2025: Senior Researcher & Tech Lead
  • Inatel – National Institute of Telecommunications, Brazil
  • Leadership of R&D projects involving Artificial Intelligence, Edge Computing, IoT, Digital Twins, and MLOps
  • Development and deployment of machine learning solutions for industrial applications
  • Technical leadership, research mentoring, and collaboration between academic and industrial teams
• 2019 – 2023: Data Scientist
  • CESAR, Brazil
  • Development of AI and machine learning solutions for industrial and enterprise applications
  • Projects involving IoT, intelligent systems, optimization, and Generative AI
  • Research and development of data-driven software solutions

Teaching & Mentoring

My teaching experience ranges from algorithms, programming, data structures, and operating systems to data science, unsupervised machine learning, and interactive computer graphics.

I have also taught Data Science and Unsupervised Machine Learning at CESAR School, including topics such as dimensionality reduction, clustering, and deep learning, using project-based learning approaches.

I am also involved in research supervision and mentoring, supporting students working on topics related to deep clustering, generative AI, graph-based learning, and intelligent systems.

• University of Coimbra
  • Unsupervised machine learning
  • Internet Technologies
  • Interactive Computer Graphics
  • Vulkan SDK and high-performance rendering
• CESAR School
  • Data Science and Unsupervised Machine Learning
  • Deep clustering, dimensionality reduction, and project-based learning
• UNIT / Unibratec / FATEC
  • Algorithms and Programming Logic
  • Data Structures
  • Computing and Programming
  • Operating Systems and Infrastructure
• Research supervision and mentoring
  • Deep clustering and graph-based learning
  • Generative AI
  • Intelligent systems
  • Machine learning and computer vision

Professional Activities

• Peer reviewer for international scientific journals
• Open-source research and software development
• Research mentoring and technical supervision
• Academic-industry collaboration
• Development of reproducible machine learning solutions

Technical Skills

• Programming: Python, C++, Java, SQL
• Machine Learning: PyTorch, Scikit-learn, Keras
• Generative AI: Hugging Face, Transformers, Unsloth, PEFT/LoRA
• Computer Vision: OpenCV
• Data Processing: PySpark, NetworkX
• Deployment & MLOps: Docker, ML production pipelines
• Research: Unsupervised Learning, Deep Clustering, Representation Learning, Explainable AI