Biography
Dr Zhu graduated with the DPhil degree in information and biomedical engineering at Oxford University in 2016. This followed her MSc in Biomedical Engineering at University College London and BSc in Electrical Engineering from the University of Malta.
Dr Zhu's DPhil focussed on the development of probabilistic techniques for combining information from wearable sensors to form a consensus that provides accurate monitoring of time-series medical data. After DPhil, Dr Zhu was awarded a Stipendiary Junior Research Fellowship at St. Hilda's College, Oxford.
In 2018, Dr Zhu was appointed as the first Associate Member of Faculty at the Department of Engineering Science; in 2019, following the award of her Royal Academy of Engineering Research Fellowship, she was appointed to full Member of Faculty at the Department of Engineering Science.
Most Recent Publications
Sepsis Mortality Prediction Using Wearable Monitoring in Low-Middle Income Countries.
Ghiasi S, Zhu T, Lu P, Hagenah J, Khanh PNQ et al. (2022), Sensors (Basel, Switzerland), 22(10), 3866
Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults.
Chun M, Clarke R, Zhu T, Clifton D, Bennett DA et al. (2022), Stroke and vascular neurology
Real-world evaluation of AI driven COVID-19 triage for emergency admissions: External validation & operational assessment of lab-free and high-throughput screening solutions
Soltan A, Yang J, Pattanshetty R, Novak A, Yang Y et al. (2022), Lancet Digital Health, 4(4), E266-E278
Digital health policy and programs for hospital care in Vietnam: scoping review
Tran DM, Thwaites CL, Van Nuil JI, McKnight J, Luu AP et al. (2022), Journal of Medical Internet Research, 24(2), e32392
Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.
Gallifant J, Zhang J, Del Pilar Arias Lopez M, Zhu T, Camporota L et al. (2022), British journal of anaesthesia, 128(2), 343-351
Research Interests
Dr Zhu’s research interests lie in machine learning for healthcare applications and she has developed probabilistic techniques for reasoning about time-series medical data. Her work involves the development of machine learning for understanding complex patient data, with an emphasis on Bayesian inference, deep learning, and applications involving the developing world.
Current Projects
- Machine learning for improving decision-making with telemedicine
- Prognosis and diagnosis of adversarial events in multimorbid population and monitoring of longitudinal treatment in multimorbid patients in both developed and developing countries
- Dynamic modelling for understanding the impact of interventions on the hospital system
- Phenotyping patients with complex diseases via electronic medical records
- Machine learning for early cancer detection as well as patient treatment response
Most Recent Publications
Sepsis Mortality Prediction Using Wearable Monitoring in Low-Middle Income Countries.
Ghiasi S, Zhu T, Lu P, Hagenah J, Khanh PNQ et al. (2022), Sensors (Basel, Switzerland), 22(10), 3866
Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults.
Chun M, Clarke R, Zhu T, Clifton D, Bennett DA et al. (2022), Stroke and vascular neurology
Real-world evaluation of AI driven COVID-19 triage for emergency admissions: External validation & operational assessment of lab-free and high-throughput screening solutions
Soltan A, Yang J, Pattanshetty R, Novak A, Yang Y et al. (2022), Lancet Digital Health, 4(4), E266-E278
Digital health policy and programs for hospital care in Vietnam: scoping review
Tran DM, Thwaites CL, Van Nuil JI, McKnight J, Luu AP et al. (2022), Journal of Medical Internet Research, 24(2), e32392
Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.
Gallifant J, Zhang J, Del Pilar Arias Lopez M, Zhu T, Camporota L et al. (2022), British journal of anaesthesia, 128(2), 343-351
DPhil Opportunities
Dr Zhu offers a wide range of machine learning projects for healthcare in both developed and developing countries. Prospective DPhil students should get in touch indicating their interest.
Most Recent Publications
Sepsis Mortality Prediction Using Wearable Monitoring in Low-Middle Income Countries.
Ghiasi S, Zhu T, Lu P, Hagenah J, Khanh PNQ et al. (2022), Sensors (Basel, Switzerland), 22(10), 3866
Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults.
Chun M, Clarke R, Zhu T, Clifton D, Bennett DA et al. (2022), Stroke and vascular neurology
Real-world evaluation of AI driven COVID-19 triage for emergency admissions: External validation & operational assessment of lab-free and high-throughput screening solutions
Soltan A, Yang J, Pattanshetty R, Novak A, Yang Y et al. (2022), Lancet Digital Health, 4(4), E266-E278
Digital health policy and programs for hospital care in Vietnam: scoping review
Tran DM, Thwaites CL, Van Nuil JI, McKnight J, Luu AP et al. (2022), Journal of Medical Internet Research, 24(2), e32392
Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.
Gallifant J, Zhang J, Del Pilar Arias Lopez M, Zhu T, Camporota L et al. (2022), British journal of anaesthesia, 128(2), 343-351
