Professional Experience

Research Associate - GECAD

GECAD (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development)

Institution: ISEP - Porto School of Engineering · GECAD

Duration: Jun 2023 – Jul 2025

Location: Porto, Portugal

Overview: As a Research Associate at GECAD, I have been deeply involved in AI-driven healthcare innovation projects, focusing primarily on data modeling, AI architecture, model training, and data manipulation. My work bridges the gap between data engineering and applied artificial intelligence, designing robust pipelines and supporting the integration of intelligent decision-support systems for healthcare and industrial optimization.

PROFIT

The PROFIT project aims to drive the digital transformation of industrial and hospital processes, emphasizing traceability, real-time monitoring, and resource optimization. Within the healthcare domain, the project focuses on the management and sterilization of reusable medical devices, particularly endoscopes, through the integration of sensors, decision support systems, and AI models.

By combining real-time data analytics with predictive modeling, PROFIT enables a more proactive and efficient management of sterilization cycles, improving safety, regulatory compliance, and device availability.

Key areas of impact:
- Remote patient monitoring, enabling continuous clinical oversight.
- Clinical Decision Support Systems (DSS) providing personalized recommendations.
- Patient engagement through intelligent, interactive tools.
- Ethical and secure use of medical data, ensuring compliance with GDPR and ISO 13485.

Links: Oficial PROFIT WebSite

RM4Health

The RM4Health project focuses on developing AI-based solutions for resource management in healthcare institutions. Its goal is to enhance operational efficiency by optimizing the allocation of medical staff, equipment, and infrastructure through intelligent data analysis and predictive modeling.

This multidisciplinary project combines healthcare engineering and artificial intelligence to create Decision Support Systems that directly impact hospital sustainability and patient outcomes.

Key areas of impact:
- Designed and trained predictive models for hospital workflow optimization.
- Developed data architectures for multi-hospital integration.
- Contributed to the design of dashboards for monitoring real-time performance.
- Collaborated with hospitals, universities, and technology partners to deploy scalable AI tools.

Links: Official RM4Health WebSite

Data Science Intern - Prozis Tech

Duration: Mar 2022 – Jul 2022

Location: Maia, Porto, Portugal

Overview: During my internship at Prozis, one of Europe’s largest e-commerce brands for nutrition and lifestyle products, I developed an AI-based churn prediction system. The project aimed to predict and explain customer churn behavior, enabling the company to identify at-risk users and deploy data-driven retention strategies.

Responsibilities:
- Implemented data cleaning, feature engineering, and exploratory analysis.
- Built machine learning models to predict customer churn probability.
- Designed interpretability methods to understand churn drivers.
- Created business dashboards for marketing and analytics teams.

Links: Prozis Tech WebSite

Technical Skills & Expertise

Artificial Intelligence & Machine Learning

As part of my master’s degree and research at GECAD, I developed expertise in:

Supervised & Unsupervised Learning: Advanced model development and implementation
Deep Neural Networks: Specialized in CNNs and RNNs architectures
Explainable AI Methods: Implementation of Grad-CAM, LIME, and Integrated Gradients
Practical Applications: Healthcare solutions, energy efficiency, and industrial optimization
Model Architecture: Design and optimization of AI systems
Performance Analysis: Rigorous evaluation and validation methodologies