I’m a Master’s student in Informatics/Software Engineering at the University of Minho, specializing in "Cryptography and Cybersecurity", and "Inteligent Systems" (Artificial Intelligence/Machine Learning). I like to think I work at the crossroads of Software Engineering, AI/ML, and Information Security, building systems that are not only smart and scalable, but also hard to break (for attackers, not for me 😅).

I aim to grow at the intersection of these fields, exploring topics such as Application Security, Penetration Testing, Threat Modeling, Secure Software Development, AI Security, Deep Learning, Natural Language Processing, Machine Learning, Data Science and DevOps. If a challenge mixes algorithms, design, security, and creativity, chances are I’ll want to dive right into it.

Machine Learning Research Fellow · March 2026 – May 2026

• Explainable AI Innovation: Spearheaded research for the AMALIA project (Portuguese LLM) aimed at transforming opaque deep learning models into transparent, mathematically readable equations.
• Model Parsing & Tensor Extraction: Engineered automated data pipelines to parse trained PyTorch and TensorFlow models, systematically extracting and cataloging weight and bias tensors across complex network layers.
• Symbolic Computing Engine: Architected a conversion engine utilizing SymPy to translate neural architectures, matrix operations, and non-linear activations (ReLU, Sigmoid, Tanh) into accurate symbolic representations.
• Algebraic Complexity Reduction: Developed and deployed advanced algebraic simplification algorithms to drastically reduce the complexity of raw model equations through systematic redundancy elimination and term grouping.
• Novel Symbolic Weight Pruning: Pioneered magnitude-based pruning strategies at the symbolic phase, surgically removing statistically insignificant coefficients to enforce sparsity and optimize equations.
• Interpretability & Optimization: Successfully delivered refined, human-readable model equations that significantly enhance architectural transparency and computational efficiency without compromising predictive accuracy.

Security Researcher · July 2025 – September 2025

• SAST & DAST Vulnerability Analysis: Executed SAST and DAST scans to identify vulnerabilities and assess application security posture across multiple services.
• OWASP Top 10 Triage & Root-Cause Investigation: Worked with engineering teams to triage, reproduce, and analyse security issues, including OWASP Top 10 findings, improving the accuracy of vulnerability root-cause investigations.
• Security Documentation & Knowledge Base Contribution: Documented debugging outcomes, testing procedures, and patch validation results, enriching the internal security knowledge base and supporting continuous learning.
• Patch & Hotfix Security Validation: Supported secure software delivery by validating patches and hotfixes, helping ensure timely remediation and alignment with secure SDLC practices.
• Security Tooling Improvement & Bug Resolution: Improved internal security tools by identifying, fixing, and optimising more than 20 issues, directly contributing to tool stability and accuracy.
• AppSec Collaboration & Continuous Learning: Engaged in team discussions and knowledge-sharing sessions, expanding exposure to application security practices and emerging threats.

Machine Learning R&D · February 2025 – December 2025

• Deep Learning Models & Advanced Architectures: Developed Deep Learning models (CNNs + Transformers) applied to semi-autonomous satellite image segmentation, integrating principles relevant to computer vision and NLP tasks based on modern architectures.
• Data Processing/automation & Integrity Engineering: Designed scripts for preprocessing, verification, and consistency checks across multi-resolution geospatial datasets, ensuring reliability and reproducibility of results.
• Definition of Evaluation Metrics: Automated training and validation pipelines, incorporating detailed analysis of loss curves and quantitative metrics (IoU, Kappa, Confusion Matrix), strengthening skills in systematic model evaluation and performance baseline establishment.
• Collaboration: I collaborated with other researchers on class definition, category merging, and auxiliary data integration, gaining experience in a multidisciplinary research environment with autonomy, critical thinking, and active contribution to applied innovation.
• Critical Analysis: I conducted in-depth analyses of class confusion and identified causes of systematic errors, consolidating practice in model diagnosis, limitation identification, and failure mitigation.
• Scientific Documentation: Production of technical documentation, reports, and presentations, ensuring clear communication of methodologies and results.
• Research Excellence Recognition: Awarded the Prémio UMinho de Iniciação na Investigação Científica 2025 (2025 UMinho Scientific Research Initiation Prize) for the work developed.

Member · October 2024 – Present

• Web, Crypto & Binary Exploitation Practice: Hands-on practice with web exploitation, reverse engineering, cryptography, binary exploitation, and forensics.
• OWASP-Aligned Vulnerability Discovery: Identified and exploited vulnerabilities aligned with the OWASP Top 10 and common application security flaws.
• Technical Write-Ups & Knowledge Sharing: Authored and shared detailed write-ups for the team, strengthening the team's internal knowledge base.
• Team-Based Offensive Security Challenges: Collaborated with teammates to solve real-world security challenges under strict time constraints, improving skills in problem-solving, communication, and teamwork.
• Research on Emerging Threats & Security Tooling: Researched and tested cutting-edge security tools and techniques, staying ahead of emerging threats.

Mestrado em Engenharia Informática (Master in Informatics Engineering)
Tracks: Cryptography & Cybersecurity · Intelligent Systems
Current Grade: 16/20
September 2025 – June 2027

BSc in Engineering Physics
Final Grade: 16/20
September 2022 – June 2025