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Dr Sharib Ali


Sharib Ali

Visiting Fellow


Dr S Ali obtained his PhD in image analysis (awarded in 01/2016) from the University of Lorraine from CNRS - CRAN laboratory in Nancy, France, where he was involved in the development of robust computer vision algorithms for monitoring bladder cancer progression by accurately creating mosaics of endoscopic videos. This work's key element was enabling the computer to match reliable features based on frame motion and perform mosaicking of the surface under observation. He did his master's research in Computer Vision at the University of Burgundy, France (2010-2012). His master's thesis was on "Retinal image analysis from fundus imaging", " a collaborative project between Oak Ridge National Laboratory, USA and Le2I, Le Creusot at the University of Bourgogne.

Dr Ali is a University lecturer (assistant professor) at the University of Leeds. Before Leeds, he worked as a post-doctoral research associate at the Department of Engineering Science, University of Oxford. During his postdoc term there, he designed robust models for computer-assisted endoscopy in gastroenterology and led most projects in endoscopy, especially the oesophageal and the colon. The work resulted in several high-quality publications and two patents (filed/submitted). The project was a part of NIHR Oxford Biomedical Research Centre imaging theme on Computer-aided endoscopy for Barrett's oesophagus, for which he worked in close collaboration with consultant gastroenterologists from the Oxford NHS University Hospitals.

Previously, he also did a postdoc at the Biomedical and Computer Vision group at the University of Heidelberg and DKFZ, Germany. During his work there, he collaborated extensively with neuroscience researchers and physicists at Forschungszentrum, J├╝lich, Germany. I designed a mathematically plausible physics-based deformable multi-modal image registration technique that allowed for precise 3D reconstruction of ultra-high resolution (1.3um) 2D histology brain images between CCD acquired image and high-throughput polarized light microscopy (more info here).


Dr S Ali's recent podcast interview highlighted the need for multimodality, multicentre approach to tackling generalisability and bias in AI for medical image analysis

Listen Here

Research Interests

  • Biomedical Image Analysis
  • Endoscopic & Surgical Computer Vision/AI
  • Early Cancer Detection
  • Intervention Patient Management Using AI in Inflammatory Bowel Disease 3D Reconstruction Augmented Reality and Virtual Reality in Medicine