Dr Peng Liu

  • Senior Lecturer
Publications
Photo of Peng

Positions

  • 09/2024-: Senior Lecturer in Statistics, Department of Mathematical Sciences, Loughborough University, United Kingdom
  • 03/2019-08/2024: Lecturer in Statistics, School of Mathematics, Statistics and Actuarial Science, University of Kent, United Kingdom
  • 11/2017-01/2019: Postdoc Fellow, Department of Mathematical and Statistical Sciences, University of Alberta, Canada
  • 08/2015-08/2017: Senior Postdoc Fellow, Department of Biostatistics, University of Washington, United States
  • 08/2015-10/2017: Postdoc Fellow, Fred Hutchinson Cancer Research Centre, United States
  • 11/2013-02/2015: Research Assistant, Department of Mathematics, Hong Kong Baptist University, Hong Kong
  • 09/2010-07/2015: PhD in Biostatistics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China
  • 09/2006-07/2010: Bachelor in Applied Mathematics, School of Mathematics and Statistics, Central China Normal University, China

Service

  • 12/2024-Now: External PhD Supervisor, School of Engineering, Mathematics and Physics, University of Kent, United Kingdom

Research philosophy and interests

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.
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 interested in the intersection of biostatistics and medical imaging data analysis, as well as protect patients privacy, the techniques that I will use includes but not limited to transfer learning, federated learning, large language models, machine learning/deep learning, survival analysis, and change point detection.

 

  • 04/2024 -Now: Lead Guest Editor, Special Issue on Explainable AI for Industrial Information Integration in Industrial IoT (IIoT), Internet of Things, Elsevier

  • 01/2024-Now: Editor in Chief, International Journal of Organizational and Collective Intelligence (IJOCI)

  • 12/2022-12/2023: Associate Editor, International Journal of Organizational and Collective Intelligence (IJOCI)

  • 12/2023: Publicity Chair (Social Sciences), 9th International Conference on Complexity, Future Information Systems and Risk (COMPLEXIS 2024), 28-29 April, 2024, Angers, France

     

  • 2022, Research and Innovation Fund, Division of Computing, Engineering, and Mathematical Sciences, University of Kent
  • 2023, UK Research and Innovation General Funds, UKRI
  • 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
  • 2023, Federated Learning based Quantile Regression Model for Credit Card Fraud Detection, Cyber Security Seedcorn Funding, Institute of Cyber Security for Society, University of Kent
  • 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
  • 2024, Google Cloud Research Credits, Google, United States

     


Current PhD students

Ms Chenxi (Maxine) Hua (September 2023 -, EPSRC studentship). Topic: Modern Change Point Detection Methods with applications to Finance, Health and Medical Imaging

Ms Ruoxue (Roxy) Duan (October 2024 -, CSC studentship). Topic: AI Methods for Public Transport-Related Carbon Emission Prediction

Mr Rongkai (Roy) Li (October 2024 -, CSC studentship). Topic: Advanced Machine Learning for Sports Injury Prevention with Wearable Tech Data

Current Postdoc

Dr Jie Li (October 2023-October 2025) Joint supervision with Prof Jian Zhang, University of Kent and Innovision IP.

Alumni

Sa (Sarah) Ren, PhD (2018-2022). First job: PDRA in Statistics, School of Health and Related Research, University of Sheffield (Thesis Topic: Inferring Network Structures Using Hierarchical Exponential Random Graph Models)