Summary
Postdoctoral researcher at the University of Oxford developing machine learning algorithms to identify disease endotypes via spatial transcriptomics and tissue imaging. Aiming to discover biomarkers, facilitate drug design, and enable personalised cancer therapy using routine histology.
Honours & Awards
- Fully funded PhD studentship (GlaxoSmithKline)
- Best Paper Award, ICCV CDpath 2021
- IT & Telecom Endowment Fund Scholarship for MSc (Pakistan HEC)
Education
PhD in Computer Science
University of Warwick, UK (2020–2024)
- Developed ML algorithms to analyse tumour microenvironment heterogeneity using spatial transcriptomics and imaging.
- Identified gene-expression and morphometric patterns for patient stratification and prediction.
- Predicted cancer drug sensitivity from histology slides, advancing AI-based personalised therapy.
- Integrated histology and multi-omics to stratify risk and identify therapeutic targets.
Experience
Postdoctoral Researcher, Computational Pathology & Spatial Omics
University of Oxford, UK (Apr 2024 – Present)
AI-based assessment of bone marrow biopsies using high-resolution histology and spatial omics.
Graduate Teaching Assistant
University of Warwick, UK (Jan 2021 – Apr 2024)
Conducted labs and seminars on data mining, AI, database systems, and programming for undergrad/postgrad students.
Lecturer, Software Engineering Department
University of Science & Technology Bannu, Pakistan (Mar 2019 – Oct 2020)
- Module leader for AI, Python programming, data structures, and architecture labs.
- Coordinated final year projects and supervised undergraduate theses.
Machine Learning Engineer
INTAQSOL, Pakistan (Feb 2019 – Mar 2019)
Predicted building 3D geometry from aerial imagery using ML techniques.
Core Competencies
- Machine Learning
- Deep Learning
- Computer Vision
- Bioinformatics
- Medical Imaging
- Pharmaco-Genomics
- Multi-Modal Data Modelling
- Graph Neural Networks
- Natural Language Processing
- Spatial Transcriptomics
Major Publications
- Dawood, M. et al. (2024). Cancer drug sensitivity prediction from routine histology images. NPJ Precision Oncology, 8(1), 5.
- Dawood, M. et al. (2023). Cross-linking breast tumor transcriptomic states and tissue histology. Cell Reports Medicine, 4(12).
- Deshpande, S., Dawood, M., Minhas, F., & Rajpoot, N. (2023). SynCLay: Interactive synthesis of histology images from bespoke cellular layouts. Medical Image Analysis, 102995.
- Lu, W., Toss, M., Dawood, M., et al. (2022). SlideGraph+: Whole slide image level graphs to predict HER2 status in breast cancer. Medical Image Analysis, 80, 102486.
- Dawood, M., Asif, A., & Minhas, F. (2020). Deep-PHURIE: deep learning-based hurricane intensity estimation from infrared satellite imagery. Neural Computing and Applications, 32, 9009–9017.
- Asif, A., Dawood, M., Jan, B., et al. (2020). PHURIE: hurricane intensity estimation from infrared satellite imagery using ML. Neural Computing and Applications, 32, 4821–4834.
Contact
Email: engrodawood@gmail.com
Phone: +44 74-05219876
LinkedIn: iamdawood
Google Scholar: a-szm64AAAAJ
ORCiD: 0000-0001-5358-9478