Ignacio Arganda‐Carreras

Timeline

1. By 2009

   A doctorate in Madrid

   Born in Madrid in 1980, he earns a BSc in computer engineering at the Autonomous University of Madrid and works as a graduate researcher in the Bioimaging Group at Lawrence Berkeley National Laboratory from 2002 to 2004. In 2009, he completes a European PhD in computer engineering and telecommunications at the same university, with a thesis on the registration and 3D reconstruction of histological sections supervised by Carlos Ortiz de Solórzano and José María Carazo.

2. 2009–2013

   Fiji and an MIT postdoc

   From 2009 to 2013, he is a postdoctoral fellow in MIT's Department of Brain and Cognitive Sciences. He is one of the founders of Fiji, an open-source distribution of ImageJ focused on biological-image analysis, and coauthors its Nature Methods paper with Johannes Schindelin and colleagues in June 2012.

3. 2012–2015

   The ISBI 2012 segmentation challenge

   With H. Sebastian Seung and other coauthors, he organizes the first international challenge on 2D segmentation of electron microscopy images of the brain, which ends with a workshop at the ISBI 2012 conference. The IDSIA team wins with a deep convolutional network, and he is first author of the 2015 Frontiers in Neuroanatomy report on the challenge.

4. 2013–2016

   Versailles postdoc and Ikerbasque fellowship

   From 2013 to 2015, he is a postdoctoral fellow in the Modeling and Digital Imaging lab of the Institut Jean-Pierre Bourgin (INRA-AgroParisTech) in Versailles. In September 2015, he becomes an Ikerbasque Research Fellow in the Department of Computer Science and Artificial Intelligence at the University of the Basque Country. Jakiunde, the Basque Academy of Science, Arts and Letters, names him a young corresponding member in 2016.

5. 2016–2017

   MorphoLibJ and Trainable Weka Segmentation

   In 2016, he coauthors MorphoLibJ, a library and plugins for mathematical morphology in ImageJ, with David Legland and Philippe Andrey. In 2017, he publishes Trainable Weka Segmentation in Bioinformatics with H. Sebastian Seung and others, a machine learning tool that trains a classifier from a limited number of manual annotations and segments the remaining microscopy data automatically.

6. April 2025

   BiaPy in Nature Methods

   In April 2025, a team he co-leads with Arrate Muñoz-Barrutia, with Daniel Franco as lead author, publishes BiaPy in Nature Methods. The open-code platform applies deep learning to biomedical image analysis and is integrated into the BioImage Model Zoo, where researchers share pre-trained models.

7. May 2026

   An RMS imaging award

   In May 2026, the Royal Microscopical Society names him winner of its Award for Data Analysis in Imaging (DAIM). The society highlights the Fiji plugins he created and his training of researchers in deep and machine learning for bioimage analysis.

8. As of October 2026

   Group leader at Biofisika

   He is a Distinguished University Researcher and Ikerbasque Research Associate Professor in the Department of Computer Science and Artificial Intelligence at UPV/EHU in Donostia-San Sebastián, also associated with the Donostia International Physics Center. He leads the BioImage Analysis and Computer Vision group at the Biofisika Institute, which develops open-source computer vision and machine learning methods for biomedical and microscopy images.