Jie Lian
Research groups
Jie Lian
Ph.D., MSc
Postdoctoral Research Associate in Machine Learning
Research Interests and Biography
Research Directions
Precision Medicine, Medical Data Science, Multimodal ML for Healthy, Health Longevity
Background
Jie Lian obtained her Ph.D. in AI in Medicine from the University of Hong Kong in 2024, funded by the Presidential Scholarship of HKU. She completed her Master’s in Data Science from the School of Informatics at the University of Edinburgh in 2019, following her Bachelor’s degree in Statistics from Northwestern Polytechnical University in 2018. From 2019 to 2020, she worked as a Research Assistant at the AutoID Labs of ETH Zurich and HSG.
Hobbies
Yoga (Professional Certificates), Guzheng
Key publications
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Early stage NSCLS patients’ prognostic prediction with multi-information using transformer and graph neural network model
Journal article
Lian J. et al, (2022), eLife, 11
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Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach
Journal article
Lian J. et al, (2024), npj Parkinson's Disease, 10
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Improving customer decisions in web-based e-commerce through guerrilla modding
Journal article
Mayer S. et al, (2021), Nature Machine Intelligence, 3, 1008 - 1010
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Metabolic biomarkers using nuclear magnetic resonance metabolomics assay for the prediction of aging-related disease risk and mortality: a prospective, longitudinal, observational, cohort study based on the UK Biobank
Journal article
Lian J. and Vardhanabhuti V., (2023), GeroScience, 46, 1515 - 1526
Recent publications
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Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach
Journal article
Lian J. et al, (2024), npj Parkinson's Disease, 10
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Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset
Journal article
Lian J. et al, (2024), BMC Infectious Diseases, 24
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Machine learning prediction of hepatic steatosis using body composition parameters: A UK Biobank Study
Journal article
Boncan DAT. et al, (2024), npj Aging, 10