About Me
My name is Huiqi Yvonne Lu. I am a passionate biomedical and machine learning engineer buzzing with ideas and aspire to real-world impact, especially in developing digital health innovations for everyone, anywhere.
Many colleagues and friends call me Yvonne (middle name) or Luqi (nickname since childhood, pronounced as lu ch-ii). Huiqi is my official first name, pronounced as Hwei ch-ii.
In my current role, I served as an academic Faculty Member, Co-chair of the researchers' committee at the Department of Engineering Science, and a Stipendiary Lecturer in Engineering Science at Worcester College, University of Oxford. I also hold an Honorary Research Fellow position at the George Institute for Global Health, Imperial College London.
In professional service, I served as an Associate Editor of Nature npj Women's Health, a Chief Editor of a 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 notable conferences, including ICLR (PMLDC), NeurIPs (ML4H), IJCAI(KDHD), and the PHME. I also actively contribute to the IEEE Standard Committee for P3191: Performance Monitoring of Machine Learning-enabled Medical Devices in Clinical Use.
Please find my institutional webpage here, and my academic "revolving-door" journey here.
About this website
This is a playground where I share my academic life, thoughts, journeys, and curiosity. I hope you find it an interesting place too.
Research Interests
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Machine learning and health foundation models
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Digital health innovations for patient monitoring
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Federated learning on Edge and generative AI accelerations
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Signal processing on time-series sensor data
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Physiological and psychological modelling with inference learning and LLMs
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Robotics and human interactions
Academic Awards and Prizes
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Best Paper Award at the International Conference on Gender and Technology. (2025)
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Runners-up of the NCRM Impact Prize 2023, National Centre for Research Methods. (2023)
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Bills and Melinda Gates Foundation Global Challenge Project Award for “Large Language Model (LLM) to Build Frontline Healthcare Worker Capacity in Rural India”. (2023)
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UK national winner of the CAETS High Potential Innovations Prizes, nominated by the Royal Academy of Engineering, UK. (2021)
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Public Engagement Champion, Computational Health Informatics Lab, University of Oxford. (2020)
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Royal Academy of Engineering Daphne Jackson Trust Career Re-entry Research Fellowship award (2019)
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National finalist of the SET for Britain, House of Commons, London, UK. (2007)
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Research Council (UKRI) Overseas Research Studentship (2005)
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Honourable Mention Award in the USA International Interdisciplinary Contest in Modelling (MCM / ICM), administered by the USA Consortium for Mathematics and Its Applications. (2003)
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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.
Publications
Lu, H.,Lu, P., Hirst, J.E., Mackillop, L., Clifton, D.A. ‘A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus’, Sensors 2023, 23, 7990.Available online at: https://doi.org/10.21203/rs.3.rs-2653408/v1
Lu, H., Ding, X., Hirst J., Yang, Y., Yang, J., Mackillop L., Clifton, D., ‘Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes’, IEEE Review of Biomedical Engineering, 2023. Available online at: https://ieeexplore.ieee.org/document/10039073
Ghadban Y., Lu, H, Adavi U., Gara, S., Ankita Sharma, A., John, R., Praveen D., Hirst, J., ‘Transforming Healthcare Education: Harnessing Large Language Models for Frontline Worker Capacity Building using retrieval-augmented generation’, NeurIPs workshop in LLM for Education, 2023. doi: 10.1101/2023.12.15.23300009
Talyor, L., Ding, X., Clifton, D., Lu, H., ‘Wearable vital signs monitoring for patients with asthma: a review,’ IEEE Sensors Journal, 02/2023. doi:10.1109/JSEN.2022.3224411 Available online at: https://ieeexplore.ieee.org/abstract/document/9967964