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Title
Huiqi Yvonne LuDPhil
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general
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a75303c052544b5bb1fc5a7ccbce6977
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https://eng.ox.ac.uk/people/huiqi-yvonne-lu
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2026-03-23T04:24:27+00:00
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Huiqi Yvonne LuDPhil

Source: https://eng.ox.ac.uk/people/huiqi-yvonne-lu Parent: https://eng.ox.ac.uk/people?c=ac

Huiqi Yvonne Lu DPhil

Dr

Associate Member of Faculty

College Lecturer in Engineering Science

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EMAIL: yvonne.lu@eng.ox.ac.uk

LOCATION: ETB 30.19

Biography

Research

Awards

Teaching

Talks

Team Members

Biography

Dr Huiqi Yvonne Lu is a researcher and a principal investigator with research expertise in AI for health informatics and computational infrastructure, a Senior Member of IEEE, and a Fellow of the Higher Education Academy. Her research focuses on multimodal time-series modelling, LLM-guided biological modelling, and federated learning (swarm intelligence) for the health monitoring of humans, machines, and the environment, especially on edge and in-network computing devices. She holds a College Lectureship in Engineering at the University of Oxford, and an Honorary Research Fellowship at the George Institute for Global Health, Imperial College London.

Yvonne completed her DPhil at the University of Sussex in pattern recognition and mobile computing, supported by the UKRI Overseas Research Scholarship and the Sussex GTA Scholarship. Her doctoral work was presented as a finalist at the SET for Britain at the UK Parliament and led to a patent.

Following her DPhil, Yvonne undertook postdoctoral research in medical device development and machine learning for biomedical imaging, including breast cancer early diagnostics with electrical impedance tomography at the Oxford John Radcliffe Hospital (funded by GE Health), automated vessel segmentation methods on colour fundus and optical coherence tomography for diabetic retinopathy at the University of Liverpool, and an oxygen-fused MRI biomarker study at the Centre of Cancer Research, University of Manchester.

After a five-year career break, Yvonne returned to academia with a Royal Academy of Engineering Daphne Jackson Fellowship at the University of Oxford (2019—2022), focusing on machine learning for maternal and chronic disease monitoring. She has since received several prestigious national and international research awards, as well as the Oxford Somerville College Fulford Junior Research Fellowship (2020—2023), Oxford MPLS Enterprise and Innovation Fellowship (2022—2023), and Oxford Saïd Business School Idea2Impact Fellowship (2023). She has led and co-led interdisciplinary AI for health projects across academia and industry. In recognition of her academic progression, she was promoted to the Associate Member of the Faculty at the Department of Engineering Science in 2023.

Dr Lu believes in the impact of an innovative end-to-end digital platform for AI for social goods, for everyone, anywhere. Therefore, in 2024, she made a strategic move from the Oxford Computational Health Informatics Lab (led by Prof David Clifton) to the Oxford Computational Infrastructure Group (led by Prof Noa Zilberman) to extend her research in federated intelligence, low-code computing, and in-network machine learning. Meanwhile, she obtained the Worcester College Lecturer in Engineering at the University of Oxford in 2024.

In professional service, Dr Lu serves organising committees for ICLR (PMLDC), NeurIPS (ML4H), IJCAI (KDHD) and is the Tutorial Co-Chair of PHME 2024 and the TPC Chair of PHME 2026. She is Associate Editor (academic) for npj Women’s Health and a Co-Editor of the special Nature collection Advances in AI for Women’s Health, Reproductive Health, and Maternal Care. She also actively contributes to the AI standard. She is a member of the IEEE Standards Committee and a key contributor to the IEEE P3191: Performance Monitoring of Machine Learning-enabled Medical Devices in Clinical Use.

Dr Lu is a STEM Ambassador and advocate for women in engineering.

Most Recent Publications

### DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

Altmetric score is

### Towards equitable AI for women's health: accessible data as a catalyst for innovation

Towards equitable AI for women's health: accessible data as a catalyst for innovation

Altmetric score is

### A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

Altmetric score is

### An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

Altmetric score is

### Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

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Research Interests

Projects

Current Projects:

Completed Projects:

Computing Infrastructure Group

Computing Infrastructure Group

Noa Zilberman

Most Recent Publications

### DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

Altmetric score is

### Towards equitable AI for women's health: accessible data as a catalyst for innovation

Towards equitable AI for women's health: accessible data as a catalyst for innovation

Altmetric score is

### A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

Altmetric score is

### An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

Altmetric score is

### Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Altmetric score is

View all

Awards

Most Recent Publications

### DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

Altmetric score is

### Towards equitable AI for women's health: accessible data as a catalyst for innovation

Towards equitable AI for women's health: accessible data as a catalyst for innovation

Altmetric score is

### A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

Altmetric score is

### An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

Altmetric score is

### Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Altmetric score is

View all

Teaching and Student Admissions

Oxford Teaching & Supervision

Most Recent Publications

### DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

Altmetric score is

### Towards equitable AI for women's health: accessible data as a catalyst for innovation

Towards equitable AI for women's health: accessible data as a catalyst for innovation

Altmetric score is

### A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

Altmetric score is

### An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

Altmetric score is

### Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Altmetric score is

View all

Keynote and Panel Talks

Talks

2026

10/03/2026, "Hospital at Home Edge: Building Low-Latency, Privacy-Preserving Patient Health Monitoring", Invited talk by Prof Qi Wang (Professor in Autonomous Systems), School of Computing and Mathematical Sciences, University of Leicester.

25/02/2026, "Building FemTech and Women’s Health in Need: Patient Health Monitoring", invited talk by Prof Kazem Rahimi and Dr Shishir Rao, Deep Medicine, Nuffield Department of Women's and Reproductive Health, University of Oxford.

15/01/2026, "From Sensors to Systems: Building Low-Latency, Privacy-Preserving Patient Health Monitoring with In-Network Machine Learning", Lightning Talk and Poster (Biomed AI and Health Theme), Oxford University MPLS AI and Ethics Conference.

2025

28/11/2025, "Building Low-Latency, Privacy-Preserving Patient Health Monitoring with In-Network Machine Learning", Oxford Digital HealthTalk: Oxbridge Women in Engineering Symposium.

01/2025, "Clinical AI and Remote Monitoring for Women with Gestational Diabetes", guest speaker at Alan Turing Institute Clinical AI meetings on AI in Women's Health. Slides

2024

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.

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.

14/06/2023 "Clinical Machine Learning and Artificial Intelligence in Medicine”, Somerville MCR-SCR symposium.

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.

09/11/2022 “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.

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 ”Machine Learning for the Next Generation of Health Informatics”, Tutorial, US Conference of the Prognostics and Health Management Society.

09/07/2020 "Machine Learning for the Next Generation of Health Informatics”, Tutorial, European Conference of the Prognostics and Health Management (PHME).

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 Lightning Presentation.

International Women in Engineering 2022

Huiqi Yvonne Lu - International Women in Engineering 2022 - University of Oxford

Most Recent Publications

### DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

Altmetric score is

### Towards equitable AI for women's health: accessible data as a catalyst for innovation

Towards equitable AI for women's health: accessible data as a catalyst for innovation

Altmetric score is

### A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

Altmetric score is

### An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

Altmetric score is

### Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Altmetric score is

View all

Dr Leago Sebesho

Leago Sebesho is a medical doctor and Rhodes Scholar pursuing an MSc in Applied Digital Health at the University of Oxford. She combines clinical experience with interdisciplinary research at the convergence of digital health and health systems.

Her work focuses on enhancing health system equity and sustainability through digital innovation. For her dissertation, she collaborates with the Department of Engineering Science on the SUSTAIN project. This project will explore methodologies for transforming unstructured multimodal healthcare data into structured data, with a focus on UK NHS primary care records.

Leago aims to shape health policy through evidence-based research and implementation strategies that strengthen healthcare delivery, particularly in resource-limited environments. Outside academia, she is committed to community engagement and youth development. She enjoys reading literature, exploring new destinations, and following sports.

Yasmina Al Ghadban

Yasmina is a third year DPhil student from Beirut, Lebanon. She is a recipient of an industrial CASE (iCASE) studentship and is mentored by an interdisciplinary team at Oxford and EMIS, as her industry partner. Prior to attending Oxford, she studied Bioengineering and Psychology at the University of Pennsylvania. She then completed the MPhil in Population Health Sciences with a focus on Health Data Science at the University of Cambridge. For her DPhil, she combines her engineering background with her passion for improving reproductive health to develop predictive models of adverse outcomes of gestational diabetes using electronic health records, and large-language models for women's health.

Maya Fayed

Maya Fayed is a Mastercard Foundation Scholar currently pursuing an MSc in Statistical Science at the University of Oxford. Her academic interests focus on developing robust, reliable computing systems that generalize across diverse and resource-constrained environments, with an emphasis on improving the performance, safety and interpretability of human-centered machine learning models. At Oxford, Maya looks forward to deepening her expertise in mathematics, statistics and computational methods, with a focus on their applications to address complex socio-technical challenges.

She graduated summa cum laude with a BSc in Computer Engineering from New York University Abu Dhabi, where she served as Engineering Representative and was recognised as a University Honours Scholar with the NYU Founders’ Day Award. Her research and projects have been largely centred on the intersection of computation and society, including developing high-resolution modelling tools for public health decision-making and applying statistical methods to evaluate causality in education policy outcomes. Prior to joining Oxford, Maya has worked in Trust and Safety, where she developed scalable data-driven systems and trustworthy models for use across the MENA region. She has also been an Equitech Scholar, applying data science towards development challenges, and volunteered with Engineers for Social Impact, where she helped advance socially responsive and community-centred approaches to technical problem-solving.

Thesis Title: Evaluating Fairness Constraints in Federated Learning with Heterogeneous Clinical Data

Omar Katkhuda

Omar Katkhuda is an MSc student in Applied Digital Health at the University of Oxford. While completing his undergraduate degree from McGill University in biotechnology and economics, he worked in market access for a diagnostics startup. Most recently, Omar worked on a project with the United Nations that integrated digital health solutions to enable remote monitoring of patients’ health status.

In his current work with the Department of Engineering Science, Omar is exploring how AI is being applied to pharmacovigilance, particularly through predictive analytics for adverse drug reaction detection and by assessing the economic value of integrating these tools into routine care.

Outside academia, he enjoys playing chess and long-distance running.

Most Recent Publications

### DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research

Altmetric score is

### Towards equitable AI for women's health: accessible data as a catalyst for innovation

Towards equitable AI for women's health: accessible data as a catalyst for innovation

Altmetric score is

### A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

A lightweight self-sensing flexible structure similar to three-bar tensegrity with superelastic SMA wires

Altmetric score is

### An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

An adaptive monitoring method for SMA wires by integrating dual resistance signals and machine learning

Altmetric score is

### Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Prediction models for maternal and offspring short- and long-term outcomes following gestational diabetes: a systematic review

Altmetric score is

View all

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