I am a researcher and scientific entrepreneur with a focus on developing interpretable machine-learning tools to enhance prediction, early identification, diagnosis, and treatment recommendations in various healthcare applications. My work spans projects like predicting adverse perinatal outcomes from fetal ultrasounds, designing antenatal risk assessment tools, and developing machine learning models to interpret echocardiographic images combined with biomarkers in cardiovascular disease.I have also led business development efforts within our research group at UPF, heading TransCOR, an AI-driven platform that leverages ultrasound imaging to support clinical decision-making in cardiology. I’m passionate about using AI to tackle real-world healthcare challenges, particularly in cardiology and obstetrics.Curious, goal-oriented, and a strong communicator, I thrive in interdisciplinary teams, collaborating closely with healthcare professionals. My work sits at the intersection of AI and healthcare, where I continuously seek to innovate and contribute to impactful, patient-centered solutions.