Dr. Sulaiman Khan
PhD, 2026
Longitudinal multimodal AI for early prediction of type 2 diabetes and its complications
Dr. Zubair Shah
Program Lead
Associate Professor, College of Science and Engineering, Hamad Bin Khalifa University
AI for health, multimodal AI and precision diabetes
About
Dr. Zubair Shah leads DAQIQ. He works on artificial intelligence for health, including large language and foundation models, multimodal AI that combines imaging, health records and omics data, and precision medicine for diabetes.
He joined HBKU in 2019 and coordinates the Master of Information Systems in Health Management program. Before HBKU he was a Research Fellow at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University. He holds a PhD in Computer Science from UNSW Canberra.
Research interests
- AI for health
- Multimodal AI
- Large language and foundation models
- Precision medicine for diabetes
- Health informatics
- Machine learning and data mining
Awards and honours
To be added
Awards, scholarships, best-paper prizes and honours with years
Projects 6
Living with Diabetes in Qatar: the LDQ Cohort
Project lead, Principal Investigator · 2026–2032ActiveAI-driven healthcare surveillance and proactive care recommendation in smart environments
Project lead, Principal Investigator · 2026–2027ActiveLongitudinal analysis of risk factors associated with diabetes using multimodal data and machine learning
PhD supervisor · 2022–2026Completed
Project lead, Principal Investigator · 2026–2032ActiveAI-driven healthcare surveillance and proactive care recommendation in smart environments
Project lead, Principal Investigator · 2026–2027ActiveLongitudinal analysis of risk factors associated with diabetes using multimodal data and machine learning
PhD supervisor · 2022–2026Completed
Publications with DAQIQ 17
The 5 most recent
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Artificial intelligence–based diabetes risk prediction from longitudinal DXA bone measurements
Khan S, Shah Z
Scientific Reports 15: 25706, 2025
Journal articleRead the paper
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Khan S, Biswas MR, Shah Z
Artificial Intelligence in Healthcare (AIiH 2025), Lecture Notes in Computer Science 16038, Springer, 2025
Conference paperRead the paper Talk and slides
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Early prediction of type 2 diabetes using multimodal data and tabular transformers
Khan S, Biswas MR, Shah Z
3rd International Conference on Foundation and Large Language Models (FLLM 2025): 592–599, IEEE, 2025
Conference paperRead the paper Free versionTalk and slides
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ECG features improve multimodal deep learning prediction of incident T2DM in a Middle Eastern cohort
Mohsen F, Safa A, Shah Z
Scientific Reports 15: 27164, 2025
Journal articleRead the paper Free version
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Integrating non-linear Radon transformation for diabetic retinopathy grading
Mohsen F, Belhaouari S, Shah Z
Scientific Reports 15: 30706, 2025
Journal articleRead the paper Free version
Talks
MICAD 202622–24 October 2026
ORCHID-DR: clinical ordinal-lesion attention with semantic prototypes for robust diabetic retinopathy grading
Dr. Zubair Shah · Edinburgh, United Kingdom
FLLM 202525–28 November 2025
Early prediction of type 2 diabetes using multimodal data and tabular transformers
Dr. Zubair Shah · Vienna, Austria
AIiH 20258–10 September 2025
DiabEye-Q: AI-driven longitudinal analysis of ophthalmoscopic images for early diabetes prediction in Qatari adults
Dr. Zubair Shah · Cambridge, United Kingdom
Supervision
Noaman Khan
PhD Student, Computer Science
Pruning and compressing large AI models for use in health
Quid Iqbal
PhD Student, Computer Science
Physics-informed neural networks for diabetes
Dr. Farida Mohsen
PhD, 2024
Multimodal deep learning for diabetes risk prediction and diabetic retinopathy grading
Dr. Md Rafiul Biswas
PhD, 2023
Natural language processing and AI for health
Teaching
- Coordinator, Master of Information Systems in Health Management (MIS-HM), since 2022
- Graduate courses in health informatics, health information privacy and security, research methods and ethics, and IT project management