I graduated in Biomedical Engineering, with a specialization in Medical Electronics, in 2022 by the University of Minho. Throughout my academic journey, I have cultivated a profound interest in advancing healthcare through the integration of technology and biomedical sciences. My academic background, coupled with hands-on research experience, has equipped me with a solid foundation in artificial intelligence, image processing, and electronics, particularly in their applications within the healthcare domain. Moreover, I have actively pursued further education in artificial intelligence and DevOps through the completion of the “Machine Learning”, “Neural Networks and Deep Learning”, “Convolutional Neural Networks” and "DevOps on AWS Specialization" courses offered by Stanford University, DeepLearningAI and AWS Web services, respectively, enhancing my skills in these critical areas. My journey into research began when I became affiliated with the Life and Health Sciences Research Institute (ICVS, School of Medicine, University of Minho) in 2021 as a Master's student contributing to the AutoFoCUS project. Following the successful completion of my Master's thesis, I transitioned into a dedicated research fellowship within the same project, a role I have held since. In this capacity, I have been exploring and implementing innovative artificial intelligence solutions tailored for automating medical training and diagnosis within the cardiac ultrasound domain. My main scientific contribution lies in my first-authored manuscript titled "Automatic multi-view pose estimation in focused cardiac ultrasound", published in the prestigious journal Medical Image Analysis (Impact Factor = 10.9). This work introduces an innovative framework aimed at automatically estimating the relative 3D pose between 2D images acquired during focused cardiac ultrasound (FoCUS) examinations. This breakthrough facilitates the application of advanced 3D image analysis methods in FoCUS, paving the way for volumetric quantification from standard 2D cardiac ultrasound views. Preliminary experiments conducted on synthetic data underscore the efficacy of this approach, demonstrating its superior performance compared to traditional 2D geometric methods currently employed in clinical practice. Additionally, I also presented my research findings at both national and international conferences. These include abstract presentations at the Congresso Português de Cardiologia, in Vilamoura, 2023, and the Portuguese Conference on Pattern Recognition (RECPAD), in Coimbra, 2023, as well as an oral presentation at the 18th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE 2023), held in Paris. Beyond academia, my personal interests and hobbies have contributed to my personal and professional development. I have been playing federated and semi-professional football since the age of four, instilling in me qualities of teamwork, discipline, and perseverance. Similarly, my decade-long engagement in swimming has further honed my focus and determination. These experiences have equipped me with invaluable soft skills that complement my academic and research endeavors.