Edgar Pinto is a PhD student in Electrical and Computer Engineering at the University of Porto, with both BSc and MSc in Biomedical Engineering (Medical Electronics specialization) from the University of Minho (UM). His research journey began in 2022 at UM's ALGORITMI Center, where he worked on optimizing organ-on-a-chip geometries. This work was recognized with the “Prémio UMinho de Iniciação na Investigação Científica” and presented at IMECE 2023. From 2023 to 2025, he was a research fellow at the Life and Health Sciences Research Institute (ICVS), School of Medicine, UM, under a grant associated with the project "Automating Analysis and Training in Focused Cardiac Ultrasound", funded by the Portuguese Foundation for Science and Technology (FCT). Currently, he is affiliated with the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) and the Applied Artificial Intelligence Laboratory (2Ai), IPCA. His master's thesis focused on benchmarking anomaly detection methods for the automatic detection of extracardiac findings in cardiac magnetic resonance (CMR) imaging, with the goal of improving diagnostic accuracy and patient care. This work yielded a journal publication in Applied Sciences (MDPI) and presentations at ICVS Retreat 2024, MIUA 2024 (Manchester, UK), RECPAD 2024 (Covilhã, Portugal), and RECPAD 2025 (Aveiro, Portugal). Prior to this, he complemented his technical background by completing the Machine Learning course offered by Stanford University and DeepLearning.AI through Coursera. Beyond his academic pursuits, Edgar has dedicated time to sports and music, having competed in federated-level soccer and learned to play piano and guitar. His research interests encompass deep learning, generative models, and unsupervised learning, with a particular emphasis on anomaly detection applied to medical image analysis.