about

Our mission, principles, and collaborators.

mission

At the heart of our mission is the ambition to revolutionise medicine through pioneering the science and adoption of computational medicine, computational phenomics, and in silico trials.

The Centre for Computational Imaging and Modelling in Medicine (CIMIM) works at the crossroads of medical image analysis and modelling, with an emphasis on machine learning and computational physiology. Through Computational Medicine, we develop computational models of disease, personalise them using complex real-world patient data, and use them to improve diagnosis, treatment, and the evaluation of medical products in cardiovascular disease, musculoskeletal disorders, and cancer.

open science

We are committed to open, transparent, and reproducible computational science. Where possible, we share preprints, source code, datasets, simulation pipelines, and the protocols underlying our in silico trials so that our work can be examined, reproduced, and extended.

Code & pipelines

Open-source code for our methods, models, and reproducible simulation pipelines on GitHub.

Preprints & papers

All publications with DOIs and open-access copies where licensing permits — see the publications page.

Datasets & reports

Datasets, technical reports, and standards work archived on Zenodo — including the InSilicoUK Landscape Report.

Researcher profiles

Find our work via Google Scholar and ORCID.

our principles

01

Empowering Breakthroughs, Together

Our Centre's collective effort and interdependence to achieve scientific excellence and impactful advancements in computational medicine.1

02

Focused Teams, Broad Impact

A strategic organisation around small, accountable teams pursuing a shared vision — making focused breakthroughs and achieving significant, wide-ranging impact across the Centre and beyond.2

03

Excellence Through Credible Ideas

A commitment to a believability-weighted idea meritocracy, where the best ideas lead the way — regardless of their source.3

  1. Frangi, AF, et al. Unlocking the Power of Computational Modelling and Simulation Across the Product Lifecycle in Life Sciences: A UK Landscape Report. InSilicoUK Pro-Innovation Regulations Network, 2023, doi:10.5281/zenodo.8325274.
  2. Wu L, Wang D, Evans JA. Large teams develop and small teams disrupt science and technology. Nature, 2019;566(7744):378–382.
  3. Dalio R. Principles: Life and Work. Simon & Schuster, 2017.

collaborators and partners

We collaborate with colleagues across the University of Manchester and beyond. Our network of academic, clinical, and industrial partners drives the translation of our research into impact.

academic collaborators

Name Affiliation Contact
Prof. Bernard Keavney University of Manchester email
Dr. Anirbit Mukherjee University of Manchester email
Dr. Tingting Mu University of Manchester email
Dr. Omar Rivasplata University of Manchester email
Dr. Ajay Bangalore Harish University of Manchester email
Dr. Seppo Virtanen University of Leeds email
Prof. Alistair Revell University of Manchester email