Personal Web page of Professor Ke Chen -- http://personal.strath.ac.uk/k.chen

This page aims to merge information from my other pages into a single one and yet show more details of research projects / highlights:
            ∎ Liverpool page, ∎ Strathclyde page and ∎ Dec 18-19, 2024 Workshop Imaging and AI Algorithms

Professor Chen is an applied and computational mathematician. His interests are in developing and analysing new and novel algorithms for a range of scientific and engineering applications. He has collaborated with many UK industries on mathematical modelling problems. More than 10 of his previous 30 PhD students worked directly with industrial funding. His current interests are in developing imaging analysis techniques for high resolution image processing problems (mainly inverse problems) using a range of mathematical tools such as variational models, PDEs, iterative solvers and deep learning methods. He has paid particular attention to medical imaging problems (such as segmentation and co-registration), engaging directly with practitioners and medical doctors. Currently he holds an honorary position at Clatterbridge Cancer Centre (NHS) as a clinical consultant.
    Prior to joining Strathclyde, he was the director of two multidisciplinary research centres (CMIT and LCMH) in the University of Liverpool. Some of his publications can be found from Google scholar, where one sees that papers published in Nature Scientific Report (2022), CVPR (2023) and SIAM IMS (2024) are from his current collaborations on Maths and AI.
Curretn research focuses on three major challeges: i segmentation and ii registration of low quality and texture images, and iii AI algorithms for few shots or self-learning segmentation.     Publications may be found on UoL page and also software
    He is keen to promote and welcome collaborations with his group and his Department where applied maths and stats are very strong.

            International Workshop on Mathematical Imaging and AI Algorithms: Dec 18-19 2024 [Registration page (Deadline: 2 Dec 2024)]

Highlights of New 2024 papers: