|
|
Title Associate Professor Contact Details Room: CS3.05
Department of Computer Science
University of 海角社区, Coventry, CV4 7AL
Tel: +44 24 7657 3801
Email: shan.raza@warwick.ac.uk |
About
Before joining 海角社区, I held a postdoctoral research position at the , where I worked on the project, funded by . My work there contributed to computational approaches for analysing tumour heterogeneity and spatial pathology in large cancer cohorts. Prior to this, I was a Research Fellow in the Department of Computer Science at 海角社区 on a 鈥�funded project investigating the origin of new beta cells during pregnancy, combining microscopy image analysis with biological discovery.
I received a BSc in Electrical Engineering from the (2008), and an MS in Systems Engineering from the (2010). I completed my PhD in Computer Science at the University of 海角社区 in 2014, where my research focused on biomedical anomaly detection using multimodal imaging. During my PhD and postdoctoral training, I also gained hands鈥憃n experience in wet鈥憀ab workflows for tissue preparation and multiplex imaging, which informs my interdisciplinary research approach.
My current research centres on computational pathology and spatial and multiplex microscopy image analysis, with a particular emphasis on quantitative characterisation of the tumour microenvironment, including spatial cellular organisation and tumour鈥搃mmune interactions. I have a strong interest in open and interoperable digital pathology. I previously led the Next鈥慓eneration File Format (NGFF) workstream as part of an Innovate UK initiative on interoperability in healthcare. I am the lead developer of , an open鈥憇ource library supporting end鈥憈o鈥慹nd AI workflows in computational pathology, and I work closely with the MONAI Pathology Working Group to support reproducible and community鈥慸riven AI research.
Research Focus
My research interests include the following areas:
-
Computational Pathology
AI鈥慸riven analysis of whole鈥憇lide histology to support quantitative tissue phenotyping, digital diagnostics, and translational cancer research.
-
Spatial and Multiplex Tissue Imaging
Analysis of multiplex and immunofluorescence imaging data to study tissue heterogeneity, spatial cellular organisation, and the structure of the tumour microenvironment.
-
Tumour Microenvironment and Spatial Tissue Analytics
Quantitative modelling of tumour-immune interactions and cell-cell spatial relationships across cancer types.
-
Computer Vision and Image Analysis Across Domains
Development and application of image analysis and visual intelligence methods, with primary focus on pathology and extensions to other imaging domains.
-
Multimodal Data Integration
Integrating imaging data with clinical, molecular, and contextual information to enable holistic understanding of disease.
-
Open鈥慡ource and Reproducible AI for Healthcare
Development of transparent, reusable, and community鈥慸riven tools for computational pathology, including open鈥憇ource software and interoperable data standards.
VISION Lab
I lead the VISION Lab (Visual Intelligence for Scalable Imaging and Open鈥憇ource iNnovation) at the University of 海角社区, which focuses on computational pathology, spatial and multiplex tissue imaging, and open鈥憇ource AI for medical imaging.
鈫�
Full details are available on the VISION Lab webpage.
Research Leadership and Funding
My research has been supported by major UK and international funding bodies including UKRI, Cancer Research UK, NIHR, Innovate UK, ERC, and the British Council. I currently serve as Principal Investigator and Co鈥慖nvestigator on multiple national and international projects spanning computational pathology, spatial tissue imaging, and open鈥憇ource AI for healthcare.
鈫�
Further details of ongoing and past projects are available on the VISION Lab webpage.
Teaching
CS324: Computer Graphics
CS424/CS904 Computational Biology
Publications
Please click for a full list of publications.
