Huiqi Yvonne Lu DPhil

Huiqi Yvonne Lu is a researcher in AI for health and sensor informatics at the Computing Infrastructure Group. She is a Stipendiary Lecturer in Engineering Science, the co-lead tutor for admissions at Worcester College, and a Fulford Junior Research Fellow at Somerville College. Yvonne serves as the co-chair of the researchers' committee and a member of the EDI 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 current research focuses on AI for health, sensor signal processing, edge intelligence, and wearable devices for health monitoring for human, machine, and environmental changes, especially digital health innovations for Femtech and non-communicable diseases such as diabetes, mental health and infectious diseases. One of her projects, SMARTedge, focuses on edge intelligence for real-time edge intelligence in autonomous driving and healthcare user cases. Another current project focuses on developing a 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 and disease discovery, thereby reducing digital health disparities, especially for LMICs. Her recent research adventure is to develop a 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 studies, 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's UK Parliament. After finishing her DPhil, Dr Lu moved on to 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 developing machine learning methods for robustly tracking patient conditions using home-monitoring systems for chronic disease, focusing on maternal health and diabetes. During her journey at the Computational Health Informatics (CHI) Lab, Dr Lu was mentored by Prof David Clifton (AI in health — Engineering Science) and Prof Lucy MacKillop (clinical — Oxford University Hospitals 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 the Faculty in 2023.

In 2024, Dr Lu joined the Computing Infrurcturer Group to extend her research in machine learning computing infrastructure and efficiency, thereby enabling end-to-end machine learning at low computing resroues in real-time. 

Dr Lu has led and co-led clinical AI and mobile biometrics projects in academic and commercial settings and filed one patent. She has served as a workshop committee member and junior round table chair at notable conferences, including ICLR (PMLDC), NeurIPs (ML4H), IJCAI(KDHD), and the PHME. Dr Lu actively contributes to the IEEE Standard Committee for P3191: Performance Monitoring of Machine Learning-enabled Medical Devices in Clinical Use. She 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.

Dr Lu is also a STEM Ambassador at the Royal Academy of Engineering and a champion for women in STEM.

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

Current Projects:

• EU Horizon Semantic Low-code Programming Tools for Edge Intelligence (SMARTEDGE) Project, Computational Infrastructure Group, Department of Engineering Science, University of Oxford. (09/2024—current)
• MItigating the Risk of developing type 2 diabetes Associated with GEstational diabetes (MIRAGE), Diabetes UK PhD Studentship, funded by Diabetes UK, UK. (2023—2026)
• Clinical study: “Gestational Diabetes Predictive Monitoring and Management“, University of Oxford, UK, in kind support by the NIHR CRN on NHS data and staff costs. (2021—2024)
• Blood Glucose Monitoring for Gestational Diabetes Health and Care: from reactive treatment to preventative medicine, Fellowship project funded by the Royal Academy of Engineering and University of Oxford. (2019—Current)

Completed Projects:

• Large Language Model (LLM) to Build Frontline Healthcare Worker Capacity in Rural India, Grand Challenge Project funded by the Bills & Melinda Gates Foundation and the George Institute for Global Health. (2023—2024)
• Oxford Saïd Business School Idea2Impact Fellowship, EMBA module of Innovation Projects and MBA module of Enterprise Finance, University of Oxford, UK. (2023)
• Enterprise and Innovation Research Fellowship, Division of Math, Physics and Life Science, University of Oxford, UK. (2021 — 2022)
• Development and validation of a non-invasive device for measuring oxygen saturation with automatic adjustment according to altitude and skin color using machine learning algorithms, Enterprise Fellowship project lead by collaborators at Peru, funded by the Royal Academy of Engineering, UK. (2021 — 2023)
• Gestational Predictive Monitoring and Management, Oxford John Fell COVID Support Fund, University of Oxford, UK. (2021 — 2022)
• Wearable Vital Signs Monitoring for Patients with Asthma, Dr Stephanie Dalley Fund for student internship, Somerville College, University of Oxford, UK. (2021)

• Joint-author Best Paper Award, International Conference on Gender and Technology. (2025)
• Runners-up of the NCRM Impact Prize 2023, National Centre for Research Methods (2023)
• Bills and Melinda Gates Foundation Global Challenge Project Award for “Large Language Model (LLM) to Build Frontline Healthcare Worker Capacity in Rural India” (2023)
• UK national winner of the CAETS High Potential Innovations Prizes, nominated by the Royal Academy of Engineering, UK. (2021) Public Engagement Champion, Computational Health Informatics Lab, University of Oxford (2020)
• Royal Academy of Engineering Daphne Jackson Trust Career Re-entry Research Fellowship award (2019)
• National finalist of the SET for Britain, House of Commons, London, UK (2007)
• Research Council (UKRI) Overseas Research Studentship (2005)
• Honourable Mention Award in the USA International Interdisciplinary Contest in Modelling (MCM / ICM), administered by the USA Consortium for Mathematics and Its Applications. (2003)
• First Prize Winner (2002) and Second Prize Winner (2003) of the China National University Student Mathematics Modelling Competition, organized by the Ministry of Education, P.R. China.

• Math (P1, A1) and Electric Electronics (P2, A2) modules: Stipendiary College Lecturer and co-lead Tutor in undergraduate admission, Worcester College, University of Oxford. (2024–current)
• Time-Series Analysis and Deep Learning module (DPhil): Lecturer and Lab demonstrator, EPSRC Centre for Doctoral Training in Health Data Science, Department of Computer Science, University of Oxford (2022)
• Mathematics in Engineering Science (2nd year UG): Tutorial Lecturer, Somerville College, University of Oxford (2022–2023)
• Medical Imaging (3rd year UG): Tutor, Department of Engineering Science, University of Oxford (2020–2021)
• Wearable Sensors (3rd year UG): Tutor, Department of Engineering Science, University of Oxford (2020–2021)
• Structural Biomaterials (MSc): Guest Lecturer of the medical imaging module, Institute of Ageing and Chronic Diseases, University of Liverpool (2015)
• Advanced Signal Processing and Analysis (MSc): Workshop supervisor, Department of Engineering and Design, University of Sussex (2006–2007)
• Digital Systems and Microprocessor (1st year UG): Lecturer (2005–2007) and lab supervisor (2004–2007), Department of Engineering and Design, University of Sussex.
• Digital Systems and Design (2nd year UG): Lab supervisor, Department of Engineering and Design, University of Sussex (2005–2006)
• Electronics (2nd year UG): Lab supervisor, Department of Engineering and Design, University of Sussex (2005–2006)
• Embedded Software Project (2nd year UG): Lab supervisor, Department of Engineering and Design, University of Sussex (2004–2006)
• UML (2nd year UG): Lab supervisor, Department of Engineering and Design, University of Sussex (2004–2005)

• 03/02/2025-07/02/2025, Session Co-Chair, Royal Academy of Engineering Frontier Symposium “Catalysing global healthcare: innovations and strategies for scalable impact”, Kenya. Slides
• 01/2025, "Clinical AI and Remote Monitoring for Women with Gestational Diabetes", guest speaker at Alan Turning Insititute Clinical AI meetings of AI in Women's Health. Slides
• 10/09/2024 "FemTech and AI for women's health", guest speaker at Cambridge Tech Week's "FemTech and the Women's Health Gap: A Sleeping Giant" meeting. This event was inspired by celebrations earlier in the year to mark 40 Years since the admission of women to Peterhouse College, University of Cambridge. Slides
• 03/07/2024-05/07/2024 "Transformers: from attention mechanisms to large language models", Tutorial Co-Chair and Speaker at PHME 2024. Slides available upon request. 
• 04/02/2024 “Craft Your Path: Using the Business Canvas for Academic Projects and Career Goals”, invited talk in the Generation Programme for the high school students, Oxford Suzhou Advanced Research Centre. Slides available upon request.
• 17/11/2023 “Machine Learning in Medical Devices for Diabetic Blood Glucose Monitoring”. Case study talk at the IEEE SA P3191 Working Group of machine learning-enabled medical device (MLMD) in clinical use. Slides available upon request.
• 14/06/2023 Somerville MCR-SCR symposium:”Clinical Machine Learning and Artificial Intelligence in Medicine”
• 03/10/2023 Freshers’ tutorial induction talk by invitation, Somerville College, University of Oxford.
• 15/02/2023 Academic outreach talk: “Machine Learning for the Next Generation of Health Informatics”, Somerville College, University of Oxford.
• 09/12/2022 Co-Chair of NCRM National Workshop of Complex clinical data and Gestational Diabetes Mellitus, Oxford, UK.
• 09/11/2022 “Clinical Machine Learning in Gestational Diabetes Monitoring”, presentation at the Daphne Jackson Trust Annual Conference, Royal Society, UK.
• 09/07/2022 “Machine learning methods — the essentials”, Tutorial at the European Conference of the Prognostics and Health Management Society. Video link.
• 23/06/2022 International Women in Engineering flash interview at the Department of Engineering Science, University of Oxford. Video link.
• 16/05/2022 Lightning talk by invitation: “Machine Learning for the Next Generation of Health Informatics – A journey in gestational diabetes”, Royal Academy of Engineering Annual Founder’s Day.
• 11/05/2022 Academic outreach talk: “Machine Learning for the Next Generation of Health Informatics”, Somerville College, University of Oxford.
• 01/12/2021 Academic outreach talk: “Machine Learning for the Next Generation of Health Informatics”, Somerville College, University of Oxford.
• 10/11/2021 Tutorial by invitation: “Challenges in Data Science Application in Healthcare”, PHME.
• 26/02/2021 Somerville MCR-SCR symposium: “Clinical Machine Learning in Patient Health and Care – at a turning point”, Somerville College, University of Oxford.
• 10/11/2020 Tutorial by invitation:”Machine Learning for the Next Generation of Health Informatics”, US Conference of the Prognostics and Health Management Society.
• 09/07/2020 Tutorial by invitation:”Machine Learning for the Next Generation of Health Informatics”, PHME.
• 09/07/2020 Standard Committee Panel Talk by invitation: “Regulatory Framework on Artificial Intelligence”, European Conference of the Prognostics and Health Management Society (PHME). Slides
• 17/11/2020 Thinktank talk by invitation: “Machine Learning for the Next Generation of Health Informatics”, UCB, Belgium. 29/06/2020 Tutorial by invitation:”Machine Learning for the Next Generation of Health Informatics”, International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2020.
• 30/05/2020 “Blood Glucose Monitoring for Gestational Diabetes Health and Care”, Oxford Women in Computer Science Lightening Presentation. Audio slides