Scholar
Cian M. Scannell
Google Scholar ID: EWjAN3YAAAAJ
Assistant Professor, Eindhoven University of Technology
Citations & Impact
Citations
1,484
H-index
14
i10-index
21
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- November 2025: Visiting Julia Schnabel’s group at TU Munich supported by the EuroTech Visiting Researcher Programme; August 2025: Co-authored the SCMR Consensus Statement on Quantitative Myocardial Perfusion MRI; June 2025: Organized a tutorial on Using Physics-Informed Neural Networks to Characterize Cardiac Properties at FIMH 2025; April 2025: New project started on developing QP-GPT: A foundation model for quantitative perfusion MRI, funded by NWO; February 2025: Obtained UTQ (university teaching qualification) certificate.
Research Experience
- Assistant Professor at Eindhoven University of Technology, focusing on medical image analysis. Working with a team of students and collaborators towards the goal of automated analysis of quantitative cardiac MRI data. Previously, held an early-career postdoc fellowship from the Wellcome/EPSRC Centre for Medical Engineering on AI-enabled quantitative cardiac magnetic resonance at King's College London.
Education
- Bachelor's degree in Mathematical Sciences from University College Cork, Ireland; PhD from King's College London, supervised by Amedeo Chiribri, focusing on using AI to automate quantitative stress perfusion cardiac MR.
Background
- Assistant Professor (tenured) in Medical Image Analysis at Eindhoven University of Technology. Primary research interest is to improve the robustness and reliability of deep learning models for medical image analysis to realize the full potential of AI in clinical practice. This includes exploring data-efficient (self-supervised, unsupervised, etc.) learning, embedding domain knowledge, understanding when AI will fail using out-of-distribution detection, and leveraging generative AI for synthetic images in model training and improving clinical data quality. Particularly interested in automated analysis of quantitative cardiac MRI data.
Miscellany
- Contact information including Email, ResearchGate, Twitter, GitHub, Google Scholar, PubMed, ORCID.
Co-authors