Martin Fergie is a machine learning and computer vision researcher at the University of Manchester in the Division of Informatics, Imaging and Data Sciences. His research interests are focussed on using machine learning models to predict disease outcomes from medical imaging data. Key projects include: predicting breast cancer risk from screening mammograms; predicting clinical outcomes for cancer using multiplex immunofluorescence tissue imaging.
Martin is currently taking part in the InnovateUK ICURe programme to identify opportunities to help relieve the workload burden on pathologists by applying artificial intelligence in clinical digital pathology.
Martin undertook his PhD at the University of Manchester 2008 - 2012 developing machine learning models for 3D human pose estimation from monocular video.
After completing his PhD, he became the Chief Technology Officer of DigitalBridge (https://www.digitalbridge.com/), a start-up applying deep learning technology for performing image understanding for indoor scenes. Martin developed the foundations of the company's technology and played a central role in building the software development and R&D teams.
Seeking a new challenge, in March 2017 he moved to the University of Manchester to apply his experience in machine learning and computer vision to help develop novel cancer imaging biomarkers. Research areas include predicting breast cancer risk from mammographic screening data and developing models for predicting clinical outcomes from histology data for follicular lymphoma and head and neck cancer. In September 2018 he was appointed as a Lecturer as part of the Integrated, Interdisciplinary, Innovations in Healthcare Sciences Hub.