Imperial College London


Faculty of EngineeringDepartment of Computing

DSI Institute Manager



k.sun Website




William Penney LaboratorySouth Kensington Campus





Dr Kai Sun is the Institute Manager of the Data Science Institute (DSI) at Imperial College London. She is also the academic WP co-lead of the IMI2 IDEA-FAST project. Her research interests include translational data management, large-scale network analysis and blockchain-based decentralised systems. 

She received PhD degree in Computing from Imperial College London in 2014. From 2014 to 2017, she was a Research Associate at the DSI, working on EU IMI projects including the Unbiased BIOmarkers in PREDiction of respiratory disease outcomes (U-BIOPRED) project and the European Translational Information and Knowledge Management Services (eTRIKS) project. From 2017 to 2018, she was the lab manager of the HNA Centre of Future Data Ecosystem, responsible for leading and managing blockchain related research projects.

She served as the local chair of the International Conference on Brain Informatics and Health (BIH 2015), local chair of the 24th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018) and the organising chair of the 1st International Conference on Mathematical Research for Blockchain Economy (MARBLE 2019).



Hoda U, Pavlidis S, Bansal AT, et al., 2022, Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort, Clinical and Translational Medicine, Vol:12, ISSN:2001-1326

Mikus MS, Kolmert J, Andersson L, et al., 2022, Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation, European Respiratory Journal, Vol:59, ISSN:0903-1936, Pages:1-17

Abdel-Aziz MI, Vijverberg SJH, Neerincx AH, et al., 2022, A multi-omics approach to delineate sputum microbiome-associated asthma inflammatory phenotypes, European Respiratory Journal, Vol:59, ISSN:0903-1936

Ng WY, Tan T-E, Movva PVH, et al., 2021, Blockchain applications in health care for COVID-19 and beyond: a systematic review, Lancet Digital Health, Vol:3, Pages:E819-E829

Nguyen T, Sun K, Wang S, et al., 2021, Privacy preservation in federated learning: An insightful survey from the GDPR perspective, Computers & Security, Vol:110, ISSN:0167-4048

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