I work at the intersection of cardiac electrophysiology, biomedical signal processing, machine learning, and biophysical modeling. My current research is centered on electrocardiographic imaging (ECGI), inverse problems, multimodal time-series learning, and noninvasive methods for cardiac assessment.
Dagoberto Mayorca Torres is a Physical Engineer with a Master’s degree in Computational Engineering and a current PhD candidate in Information and Communication Technologies at the University of Granada. His work combines artificial intelligence, biomedical signals, scientific computing, and applied modeling.
Alongside his academic role at Universidad Mariana, he has contributed to higher education and content development for institutions such as Universidad Internacional de La Rioja, MIU City University Miami, Florida Global University, Universidad Cooperativa de Colombia, and other research and teaching initiatives.
Broader interests include IoT, cloud computing, numerical modeling, image processing, edge computing, and data-driven methods for engineering applications.
Systematic review of computational techniques, dataset utilization, and feature extraction in electrocardiographic imaging
Open full publication list →Noninvasive cardiac imaging, ECGI reconstruction, and data-driven methods that combine temporal modeling with physically meaningful constraints.
See research projects →Teaching in engineering, machine learning, programming, image processing, and graduate supervision in AI and computational engineering.
See teaching and supervision →