Rate My Professor Sharib Ali

Dr. Sharib Ali is an Associate Professor in the School of Computer Science at the University of Leeds, where he founded and leads the AI in Medicine and Surgery (AIMS) group. With over 15 years of experience in medical, biomedical, and surgical data analysis focused on imaging and computer vision, Ali has made significant contributions to artificial intelligence in healthcare. He obtained a Master’s degree by research in Computer Vision from the University of Burgundy, France (2010-2012), with a thesis on retinal image analysis from fundus imaging in collaboration with Oak Ridge National Laboratory, USA. He was awarded a PhD in image analysis from the University of Lorraine, France (2016), for developing robust computer vision algorithms to monitor bladder cancer progression via endoscopic video mosaicking. His career trajectory includes postdoctoral research at the Biomedical and Computer Vision group under Prof. Karl Rohr at the University of Heidelberg and German Cancer Research Center (DKFZ), Germany (2015-2018), and at the Department of Engineering Science, University of Oxford (2018-2022), where he retains a visiting fellow position. Ali joined the University of Leeds as a lecturer (assistant professor) in 2022 before his promotion to Associate Professor.

Ali’s research interests include computer vision, machine learning, medical and biomedical image analysis, computational endoscopy and surgery, multi-modal data diagnosis, segmentation, 3D reconstruction, and tracking. As principal investigator, he leads projects such as Artificial Intelligence for Surgical Training Towards Safer Sub-mucosal Dissection, Leveraging Multi-modality Data for Targeted Biopsy and Risk Stratification in Inflammatory Bowel Disease, and Real-time High-Fidelity Augmented Reality in Laparoscopic Liver Resection. Notable awards encompass recognition among the Elsevier and Stanford World’s Top 2% Scientists (2023-2025), Academy of Medical Sciences Springboard Award 2025 (£125,000 for AI solutions in early bowel cancer detection), EPSRC New Investigator Award 2025, and Worldwide Universities Network research grants (2024-2025). Key publications include “A deep learning framework for quality assessment and restoration in video endoscopy” (Medical Image Analysis, 2021), “FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation” (IEEE Transactions on Neural Networks and Learning Systems, 2022), “Meta-learning with implicit gradients in a few-shot setting for medical image segmentation” (Computers in Biology and Medicine, 2022), and “A multi-centre polyp detection and segmentation dataset and baseline” (Scientific Data, 2023). Ali influences the field as initiator and organizer of endoscopic computer vision challenges since 2019, P2ILF challenge at MICCAI 2022, and workshops on cancer prevention at MICCAI; general chair of MIUA 2025; programme committee for IEEE CBMS 2024; reviewer for journals like IEEE TPAMI, Nature Communications, and Medical Image Analysis; and committee member for Royal Society Newton International Fellowships. He also serves as a volunteering adjunct research scientist at NAAMII, Nepal.