I am currently pursuing a Doctorate in Business Administration (DBA) at Iscte - Instituto Universitário de Lisboa, focusing on the cost-effectiveness and value-based health assessment of medical technologies. Additionally, I am a research assistant at the Business Research Unit (BRU-Iscte) specifically within the data analytics group of Iscte - Instituto Universitário de Lisboa.

I hold both a bachelor’s and a master’s degree in biomedical engineering, specializing in image processing and signal processing. My projects include the automated detection of retinopathy using MATLAB and leveraging chaotic features of EEG signals for autism detection using genetic algorithms. To complement my technical expertise, I pursued an MBA, gaining a foundation in strategic management, financial analysis, and healthcare economics.

With nine years of experience in the cardiovascular medical device industry, I have been involved in implementing cardiovascular technologies, including clinical validation, regulatory compliance, and market adoption. My hands-on experience also includes training physicians and navigating the challenges of translating research into clinical practice.

My research interests lie at the intersection of artificial intelligence (AI), machine learning (ML), and healthcare management, with a focus on improving healthcare delivery and reducing costs. I explore how these technologies can enhance patient outcomes, optimize healthcare expenses, and support evidence-based decision-making. Through comprehensive clinical and economic evaluations, my work provides valuable insights to inform healthcare policies, investments, and strategic decisions, ensuring that innovative medical technologies are both clinically effective and economically sustainable.

My PhD thesis focuses on the cost-effectiveness and value-based health assessment of an AI-powered ECG library for cardiovascular disease prediction. In collaboration with CardioID, a Portuguese company specializing in advanced ECG analytics for early detection and risk assessment of cardiovascular diseases, and Santa Marta Hospital, this project aims to transform early detection and risk stratification of cardiovascular diseases using cutting-edge machine learning algorithms applied to ECG data.

Through this project and my broader research endeavors, we are committed to developing cost-effective, scalable healthcare solutions, aiming to expand this initiative to additional hospitals.

Key Skills and Techniques:

• Machine learning algorithms

• MATLAB

• Python

• Statistical modeling

• Signal processing

• Image processing

• Healthcare economics

• Cost-effectiveness analysis

• Research skills

• 10-month grant for the 2024-2025 Development of Pedagogical and Scientific Skills Grant from ISCTE Business School, supporting further development of my academic and research capabilities.