BEng (Hons), MSc, PhD
NOVO NORDISK POSTDOCTORAL RESEARCH FELLOW
Taiyu Zhu has completed his Ph.D. degree in Electrical and Electronic Engineering at Imperial College London in 2022. He received the First-Class B.Eng. degree (Hons) from Australian National University, in 2017, and the Distinction M.Sc. degree from Imperial College London, in 2018. He was a recipient of the President’s Ph.D. Scholarship and was awarded the Outstanding Achievement Award and the Stylianos Kalaitzis PhD Award, the most promising doctoral work, at Imperial College London.
His research interests include biomedical signal processing, data science, and artificial intelligence (AI), especially machine learning and deep learning, in healthcare, aiming to deliver cutting-edge biomedical applications and novel AI-powered technologies to improve the health and well-being for people with chronic cardiometabolic diseases.
He was awarded the Novo Nordisk Postdoctoral Research Fellowship, to work with Associate Prof Alejo Nevado-Holgado, Dr Joanna Howson, Dr Sile Hu, and Dr Robert Kitchen, starting in January 2023. His fellowship project, titled “Integrating genetics and deep neural networks to identify future drug targets for cardiometabolic disease”, aims to leverage AI techniques, especially deep learning, and large human genomic datasets to identify potential causal genes for cardiometabolic traits, assess their viability as potential therapeutic targets, and validate the hypothesised targets in phenotypic assays.
Offline Deep Reinforcement Learning and Off-Policy Evaluation for Personalized Basal Insulin Control in Type 1 Diabetes.
Zhu T. et al, (2023), IEEE J Biomed Health Inform, PP
A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q-Learning to Improve Type 1 Diabetes Management
Noaro G. et al, (2023), IEEE Journal of Biomedical and Health Informatics, 1 - 10
GluGAN: Generating Personalized Glucose Time Series Using Generative Adversarial Networks
Zhu T. et al, (2023), IEEE Journal of Biomedical and Health Informatics, 1 - 12
Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.
Zhu T. et al, (2022), IEEE transactions on bio-medical engineering, PP
Enhancing self-management in type 1 diabetes with wearables and deep learning.
Zhu T. et al, (2022), NPJ digital medicine, 5