"I’m pleased to welcome you to the Cambridge Image Analysis Group (CIA). Here, we blend mathematics and innovation to solve impactful problems in imaging, machine learning and in a diverse range of applications. Join us on this exciting journey of discovery. Welcome to the CIA!"
— Professor Carola-Bibiane Schönlieb
Welcome to the Cambridge Image Analysis (CIA) Group in DAMTP. Our group specialises in theory and methodology development to solve intricate problems, ranging from digital image and video processing to inverse problems and partial differential equations, optimisation algorithms, mathematical modelling, and machine learning. Explore with us as we harness the strength of mathematics to unravel complexities and pave the way for groundbreaking solutions.
Some topic we work on:
- Inverse problems
- Variational methods and partial differential equations
- Image restoration
- Image segmentation and object tracking
- Image registration and motion compensation
- Mathematical foundations of machine learning
- Semi-supervised learning, reinforcement learning etc.
- Graph and hypergraph learning
- Computer vision including low-level vision
- Optimisation (e.g., learning to optimise techniques)
- Generative AI (diffusion models, GANs, normalising Flows)
- We are interested in a wide range of applications including:
- Biomedical imaging (e.g.,MRI, PET/SPECT, microscopy imaging)
- Computational photography
- Full blood counts
- Arts restoration
- Remote sensing
- Traffic flow analysis
- Large scale computing
- Multi-modal analysis
For more information on current research projects, please visit our research page and the project websites for the Cambridge Mathematics of Information in Healthcare Hub (CMIH) and the Cantab Capital Institute for the Mathematics of Information (CCIMI), Blood Counts and Mathematics of Deep Learning (Maths4DL).
This group is mainly funded by EPSRC, the Leverhulme Trust, the Newton Trust, 