About Me
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 Professors 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.
Experience
2024 - present
Postdoctoral Scientist in Cardona’s lab at MRC Laboratory of Molecular Biology (LMB)
2019 - 2024 (4 years, 11 months)
PhD at University of the Basque Country (UPV/EHU)
2015 - 2024 (9 years, 1 month)
HPC Resources Technician at Donostia International Physics Center (DIPC)
2022 (6 months)
PhD Intern at Harvard, advised by Prof. Donglai Wei and Prof. Hanspeter Pfister
2018 - 2019 (1 year)
Master’s degree in Computational Engineering and Intelligent Systems
2011 - 2015 (4 years)
Bachelor’s degree in Computer Engineering
2014 (6 months)
Company practices at Donostia International Physics Center (DIPC)
Publications
2024
Nature Machine Intelligence
A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features
Davide Carnevali, Limei Zhong, Esther González-Almela, Carlotta Viana, Mikhail Rotkevich, Aiping Wang, Daniel Franco-Barranco, Aitor Gonzalez-Marfil, Maria Victoria Neguembor, Alvaro Castells-Garcia, Ignacio Arganda-Carreras, Maria Pia Cosma
2024
IEEE ISBI
2024
bioRxiv
BiaPy: Accessible deep learning on bioimages
Daniel Franco-Barranco, Jesús A Andrés-San Román, Ivan Hidalgo-Cenalmor, Lenka Backová, Aitor González-Marfil, Clément Caporal, Anatole Chessel, Pedro Gómez-Gálvez, Luis M Escudero, Donglai Wei, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2023
A&A
2023
IEEE ISBI
2023
IEEE ISBI
2023
IEEE TMI
Current Progress and Challenges in Large-scale 3D Mitochondria Instance Segmentation
Daniel Franco-Barranco, Zudi Lin, Won-Dong Jang, Xueying Wang, Qijia Shen, Wenjie Yin, Yutian Fan, Mingxing Li, Chang Chen, Zhiwei Xiong, Rui Xin, Hao Liu, Huai Chen, Zhili Li, Jie Zhao, Xuejin Chen, Constantin Pape, Ryan Conrad, Jozefus De Folter, Luke Nightingale, Martin Jones, Yanling Liu, Dorsa Ziaei, Stephan Huschauer, Ignacio Arganda-Carreras, Hanspeter Pfister, Donglai Wei
2023
Cell Reports Methods
CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia
Jesús A. Andrés-San Román, Carmen Gordillo-Vazquez, Daniel Franco-Barranco, Laura Morato, Antonio Tagua, Pablo Vicente-Munuera, Ana M. Palacios, Maria P. Gavilan, Valentina Annese, Pedro Gómez-Gálvez, Ignacio Arganda-Carreras, Luis M. Escudero
2022
CMPB
Deep learning based domain adaptation for mitochondria segmentation on EM volumes
Daniel Franco-Barranco, Julio Pastor-Tronch, Aitor González-Marfil, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2022
Cell Systems
A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia
Pedro Gómez-Gálvez, Pablo Vicente-Munuera, Samira Anbari, Antonio Tagua, Carmen Gordillo-Vázquez, Jesús A. Andrés-San Román, Daniel Franco-Barranco, Ana M. Palacios, Antonio Velasco, Carlos Capitán-Agudo, Clara Grima, Valentina Annese, Ignacio Arganda-Carreras, Rafael Robles, Alberto Márquez, Javier Buceta, Luis M. Escudero
2021
Computer Methods and Programs
in Biomedicine
2021
Neuroinformatics
Stable deep neural network architectures for mitochondria segmentation on electron microscopy volumes
Daniel Franco-Barranco, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2020
MICCAI