Qiang Zhang

PhD, FSCMR

Associate Professor of AI in Cardiovascular Imaging

British Heart Foundation Intermediate Fellowship
Deputy Lead, RDM AI and Medical Big Data CCRT

I am a machine learning scientist working on AI for cardiovascular imaging and population health, based at the Division of Cardiovascular Medicine and Big Data Institute.

My research programme focuses on two complementary areas:

(i) Advancing cardiovascular MRI with deep learning. A representative work is Virtual Native Enhancement (VNE) imaging, where we developed AI techniques that could serve as "virtual contrast" in enhancing MR images, without the need for contrast injections. This technology may lead to more informative, needle-free, faster and safer heart MR scans.

(ii) Studying cardiovascular and cardiometabolic disease through the lens of machine learning and large-scale medical and population data. The goal is to improve cardiovascular population health through AI-enhanced biomarkers and data-driven approaches for risk stratification, prediction and disease prevention.

In the press

• RDM News: "First real-world trial shows AI could reduce contrast injections ...", 15 Jul 2026
• The Sunday Times: "AI slashes cost of MRI scans ...", 1 Jan 2023
• Oxford University News: "How AI is shaping medical imaging", 20 Sep 2022
• RDM News: "SCMR Early Career Award" 8 Feb 2022
• BHF News: "AI breakthrough for faster, cheaper and injection-free heart scans", 9 Aug 2021
• The Telegraph: "New AI heart scanner will cut NHS backlog ...", 7 Aug 2021
• SCMR Newsletter, 29 Jul 2021
• OUH News: "AI replaces contrast dye for fast, cheaper ...", 8 Jul 2021
• RDM News "AI breakthrough for fast and cheaper CMR scans", 7 Jul 2021
• NIHR Oxford BRC News: "AI replaces contrast dyes for needle-free CMR", 7 Jul 2021

• BBC Radio 4 Today Interview, on how new AI technologies can help with NHS backlog, 9 Aug 2021
• Times Radio Interview, on AI and robotics in healthcare, 10 Aug 2021