Our group is dedicated to bridging the gap between cutting-edge mathematical research in imaging, AI, and inverse problems and broader audiences. Through videos, articles, public lectures, and collaborative initiatives, we aim to inspire curiosity about how mathematics powers real-world applications—from restoring ancient artefacts to advancing healthcare and environmental conservation. This page highlights key outreach activities, including contributions from CIA members and affiliated projects.
Videos and Talks
Explore engaging talks and demos that demystify mathematical imaging. These resources are ideal for students, educators, and enthusiasts.
| Title | Description | Link |
|---|---|---|
| Mathematical Moments: Carola-Bibiane Schönlieb | A short interview where Prof. Schönlieb shares her passion for image analysis, favourite "aha" moments in maths, and why creativity fuels discovery. | Watch on plus.maths.org (embedded video) |
| Women of Mathematics: Carola-Bibiane Schönlieb | Personal stories and career reflections from Prof. Schönlieb, highlighting the challenges and joys of being a woman in math. | YouTube |
| Mathematical Imaging: From Geometric PDEs to Deep Learning | Prof. Schönlieb's plenary at EMS Women in Mathematics Day 2024, covering image denoising, segmentation, reconstruction, and hybrid AI-PDE models for biomedical and conservation applications. | YouTube |
| Inverse Problems in Imaging: From Differential Equations to Deep Learning | EPFL Seminar Series in Imaging. | YouTube |
| Image Inpainting Demo | Various image inpainting methods are demonstrated, removing the sticks from the image with various levels of success. | YouTube |
| Mathematical Approaches to Image Processing with Carola Schönlieb | This video covers mathematical approaches to image processing. | YouTube |
| Inverse problems in imaging and machine learning – Ferdia Sherry | Ferdia explains how bilevel optimisation problems pop up when learning parts of a variational model and how this approach is used to learn a sampling pattern for MRI. | YouTube |
Articles
In-depth reads showcasing the societal impact of our work.
- Dynamical systems-based neural networks with increased robustness: In a long-standing collaboration between the DNA group at NTNU and the CIA group at the University of Cambridge, we have been doing research in the field of structure-preserving deep learning (Celledoni et al., 2021). A major topic within this field is concerned with drawing connections between dynamical systems and neural networks. In this blog post, we discuss this topic, focusing on its use in designing stable neural networks.
Read here - Understanding the Diversity of Forests Using AI: Prof. Schönlieb discusses semi-supervised ML for analysing aerial images to map tree species, aiding conservation in India.
Read here - Women of Mathematics: Carola-Bibiane Schönlieb: Profile on her journey in applied math, emphasising diversity and computational analysis.
Read here
Events and Public Engagements
Highlights from lectures, festivals, and high-profile visits.
- Maths or Medicine – Which Comes First?: Panel with Prof. Schönlieb and Prof. John Aston on how math revolutionises healthcare (e.g., stats in drug trials) and vice versa. Explored cross-disciplinary inspirations.
Event Details - Ministerial Visit: Exploring AI for Societal Good: UK Government minister Rt Hon Pat McFadden MP visited Cambridge to discuss AI's role in healthcare. Prof. Schönlieb showcased the "BloodCounts!" project, using AI to accelerate blood disorder diagnoses—emphasising ethical, explainable models for public benefit.
Feature Article
Collaborations and Initiatives
- HER MATHS STORY (hermathsstory.eu): An inspiring platform sharing personal narratives of women in mathematics to foster diversity and mentorship
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