Dr Huiqi Yvonne Lu

Huiqi Yvonne Lu is a biomedical data scientist, an Associate Member of Faculty and the Co-Chair of Researchers Committee at the Department of Engineering Science, University of Oxford. She also holds an honorary Research Fellow position at the George Institute for Global Health, Imperial College London. Her research focuses on clinical machine learning, sensor signal processing, and wearable devices for patient monitoring, especially on digital health innovations for global women’s health and chronic health conditions such as diabetes. Her current research interest is to develop health foundation model for time-series data, and exploring the feasibility of using meta-learning with large language models for explainable AI for health monitoring, disease discovery, thereby reduce digital health disparities, especially for LMICs. One of her recent research adventures is to develop reasoning-informed model to enhance clinical capacity in India using large language models, funded by the Bills and Melinda Gates Foundation Global Challenge Grant and the George Institute for Global Health.

Dr Lu obtained her DPhil in mobile computing and pattern recognition at the Centre of Signal Processing and Industrial Informatics, University of Sussex, UK, sponsored by the UKRI Oversea Research Student Scholarship and the Sussex GTA Scholarship. During her doctoral study, she developed a commercial iris-identification system for mobile devices, which led to a patent and her work was presented at the SET for Britain, UK Parliament. After finishing her DPhil, Dr Lu moved onto the biomedical & clinical research on electrical impedance tomography for breast cancer at the Oxford John Radcliff Hospital (funded by GE Health) and diabetic retinopathy imaging at the Institute of Chronic Diseases, University of Liverpool.

In 2019, after a five-year career break, Dr Lu joined the Institute of Biomedical Engineering at the University of Oxford with a Daphne Jackson Trust Career Re-entry Research Fellowship, sponsored by the Royal Academy of Engineering and the University of Oxford. Her Fellowship project focused on the development of machine learning methods for robustly tracking patient condition using home-monitoring systems for chronic disease, with a special focus on maternal health and diabetes. During her journey at the Computational Health Informatics (CHI) Lab, with great honour, Dr Lu was mentored by Prof David Clifton (AI in health — Engineering Science) and Prof Lucy MacKillop (clinical — Oxford University Hospitals and and industrial — EMIS Health). She was honoured to attain the Somerville College Fulford Junior Research Fellowship (2020-2023), the Oxford MPLS Enterprise and Innovation Research Fellowship (2021-2022), and the Oxford Saïd Business School Idea2Impact Research Fellowship (2023). In recognition of her academic progression, she was promoted to the Associate Member of Faculty in 2023. Dr Lu has led and co-led clinical AI and mobile biometrics projects in both academic and commercial settings, and filed one patent.

Dr Lu is an Associate Editor of Nature npj Women’s Health, a Chief Editor of the special collection of Advances in AI for women’s health, reproductive health, and maternal care: bridging innovation and healthcare, and a guest editor of Frontier Signal Processing. She has served as a workshop committee member and junior round table chair at at notable conferences, including ICLR (PMLDC), NeurIPs (ML4H), IJCAI(KDHD), and the PHME. Dr Lu is an active contributor in the IEEE Standard Committee for P3191: Performance Monitoring of Machine Learning-enabled Medical Device in Clinical Use.

Dr Lu is also a Royal Academy of Engineering STEM Ambassador (2020 — current).

• Machine learning and health foundation models
• Digital health innovations for patient monitoring
• Signal processing on time-series sensor data
• Physiological and psychological modelling with inference learning and LLMs
• Robotics and human interactions