Daniel Franco-Barranco is a dedicated researcher specializing in biomedical image processing and computer vision, with a primary focus on the development of deep learning solutions for the segmentation of organelles in large-scale and multimodal electron microscopy images.

He earned his Ph.D. in Computer Science from the University of the Basque Country (UPV/EHU) under the mentorship of Prof. Ignacio Arganda-Carreras and Prof. Arrate Muñoz-Barrutia. During his doctoral studies, he also worked as an HPC Resources Technician at the Donostia International Physics Center (DIPC), where he managed and configured the largest computational cluster in the Basque Country.

In 2022, Daniel completed a six-month research internship at Harvard University, supervised by Professors Donglai Wei and Hanspeter Pfister.

Currently, he is a Postdoctoral Scientist in Dr. Albert Cardona’s group at the MRC Laboratory of Molecular Biology (LMB). His research focuses on developing automated techniques for mapping connectomes from volumetric electron microscopy data. This work aims to elucidate the neuronal basis of behavior by comparing connectomes across experimental conditions, developmental stages, and species. Daniel’s role involves designing novel machine learning approaches for computer vision, applying these methods at scale across multiple brain volumes, and contributing to the scientific community through presentations, publications, and the mentorship of junior researchers.