Rate My Professor Jianing Qiu

Jianing Qiu is Assistant Professor of Personalized Medicine at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). His research addresses practical needs and challenges in medicine and healthcare through AI technologies. He is passionate about interdisciplinary research that creates insights and solutions for advancing global health innovation and medical breakthroughs, with the aim of realizing personalized medicine. His current research interests include agentic medical AI, medical foundation models, and embodied medical AI.

Prior to joining MBZUAI, Professor Qiu was a postdoctoral research fellow in the Department of Biomedical Engineering at The Chinese University of Hong Kong. He received his Ph.D. from the Department of Computing at Imperial College London in 2023, following an M.Sc. in Computing Science (Distinction), also from Imperial College London. During his Ph.D., he was affiliated with the Hamlyn Centre for Robotic Surgery and the Institute of Global Health Innovation and completed an internship at Tencent. Professor Qiu has served as guest editor for the IEEE Journal of Biomedical and Health Informatics (Special Issue on Biomedical and Health Foundation Models) and Frontiers in Digital Health. He organized the first Agentic AI in Medicine workshop at MICCAI 2025 and was a key organizer of workshops on wearable intelligence and embodied AI agents for healthcare at ICRA 2024, ECCV 2024, and CVPR 2025. His work has been published in leading journals including NEJM AI and Nature Machine Intelligence and has received coverage in major news outlets. He received the Most Innovative Student Paper Award at the 16th IEEE BSN Conference. Key publications include “Large ai models in health informatics: Applications, challenges, and the future” (IEEE Journal of Biomedical and Health Informatics, 2023), “Development and validation of a multimodal multitask vision foundation model for generalist ophthalmic artificial intelligence” (NEJM AI, 2024), and “LLM-based agentic systems in medicine and healthcare” (Nature Machine Intelligence, 2024).