I recognise that interdisciplinary research offers greater opportunities for scientific and technological breakthroughs since the world is diverse and statistics\/biostatistics alone can not address all problems in isolation.<\/p>\n
My research interest lies in the intersection of machine learning and statistics. My general focus is to apply machine learning techniques to improve traditional statistical methodologies\/overcome the existing bottleneck of statistical procedures and introduce statistical ideas in machine learning. Currently, I’m focused on developing non-computationally intensive matrix factorisation techniques and applying these techniques to solve practical problems. I’m also interested in protecting each individual’s privacy when analysing sample data, especially the differential privacy technique where statistical random errors are added when sharing information about a dataset. I have actively collaborated with professors in statistics, electrical engineering, and industry, such as the Huawei company in Canada and Hong Kong.<\/p>\n
In addition, my research area includes Reinforcement Learning, High Dimensional Data, Bridging Study, Functional Data Analysis, Biostatistics, Semiparametric Modelling, Causal Inference, and Rank Estimation.<\/p>\n
2024, Mr Lu Zhang, School of Business, Chizhou University, Chizhou, China (18 Feb – 7 Jul)<\/p>\n
2023, Professor Feipeng Zhang, School of Finance and Economics, Xi’an Jiaotong University, Xi’an, China (27 Mar – 25 May)<\/p>\n
2023, Mr Bo Pan, Biostatistician, Epidemiology Coordinating and Research (EPICORE) Centre, University of Alberta, Edmonton, Canada<\/p>\n
2023, Dr Yafei Wang, Lecturer in Statistics, Department of Mathematical Sciences, University of Essex, Colchester, United Kingdom<\/p>\n
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2022, Research and Innovation Fund, Division of Computing, Engineering, and Mathematical Sciences, University of Kent<\/p>\n
2023, UK Research and Innovation General Funds, UKRI<\/p>\n
2023, Improving the statistical analysis of brain imaging data to generate more accurate descriptions of brain activity, UK Research and Innovation, Knowledge Transfer Partnerships (KTP) Fund<\/p>\n
2023,\u00a0Federated Learning based Quantile Regression Model for Credit Card Fraud Detection,\u00a0Cyber Security Seedcorn Funding, Institute of Cyber Security for Society, University of Kent<\/p>\n
2024, Exploring the application of Large Language Models in Medical Image Analysis: Integrating Statistics to Ensure Fairness and Privacy Protection, Networking Fund, The Academy of Medical Science, United Kingdom<\/p>\n
2024, Google Cloud Research Credits, Google, United States<\/p>\n","protected":false},"excerpt":{"rendered":"
I recognise that interdisciplinary research offers greater opportunities for scientific and technological breakthroughs since the world is diverse and statistics\/biostatistics alone can not address all…<\/p>\n