Daniel Franco-Barranco Defends His PhD on Deep Learning for Bioimage Analysis

🎉 We are thrilled to announce that Daniel Franco-Barranco has successfully defended his PhD thesis on June 21, 2024 at the University of the Basque Country (UPV/EHU)! 🎉

Daniel’s thesis, titled “Deep Learning for Bioimage Analysis: novel user- and developer-oriented approaches”, explores the transformative role of deep learning in the field of biological imaging—from robust and scalable segmentation pipelines to open-source tools that make advanced AI accessible to researchers worldwide.

The defense committee was composed of:

• 🧠 Gorka Azkune - HiTZ Center - Ixa, University of the Basque Country
• 🔬 Anatole Chessel - Laboratory for Optics and Biosciences, École Polytechnique, France
• 🧬 Virginie Uhlmann - Director of the BioVisionCenter, University of Zurich (participated remotely)

Daniel was supervised by Ignacio Arganda-Carreras (UPV/EHU, DIPC, Biofisika Institute) and Arrate Muñoz-Barrutia (UC3M, IISGM), and his work bridges AI, microscopy, and life sciences. His contributions include:

• Developing reproducible and robust deep learning models for biological image segmentation
• Designing novel domain adaptation strategies for multi-modal datasets
• Creating and curating the MitoEM dataset and challenge for benchmarking mitochondria segmentation
• Leading the development of BiaPy, an open-source deep learning platform for scalable and user-friendly bioimage analysis
• Applying these methods to real-world biological studies, including epithelial cyst segmentation and label-free cell imaging

👏 Congratulations, Daniel, on this fantastic achievement and for pushing the frontiers of deep learning in bioimaging! We look forward to seeing what comes next in your research journey.