Fully funded PhD studentship: deep extreme value learning for landslide tail risk. Apply by 13 January 2027.
My work sits where statistical theory meets the data that real problems actually produce: observations that are incomplete, distributions with heavy tails, and records too sensitive to pool in one place.
Quantile and extreme-value methods
Averages describe the typical case, but decisions usually turn on the rest of the distribution. I work on quantile and expectile regression for functional, incomplete, and high-dimensional data; expectile-based threshold autoregressive models; and extreme value theory for the tail events that dominate risk, currently including landslide risk under a changing climate.
Survival and event-history analysis
Time-to-event data are rarely observed cleanly. I develop estimators that stay valid under right censoring, left truncation and length-biased sampling, covering quantile residual lifetime, the proportional odds model under right truncation, recurrent gap times, and frailty models for clustered failure times.
Trustworthy AI for health and risk
Clinical and financial records are often too sensitive to centralise. I work on federated learning and privacy-preserving estimation, on fairness and privacy for large language models applied to multimodal medical data, and on applications from neuroimaging and rehabilitation technology to credit card fraud detection.
2025, Dr Akarsh K Nair, Indian Institute of Information Technology, India (from 1 Aug)
2024, Mr Lu Zhang, School of Business, Chizhou University, Chizhou, China (18 Feb – 7 Jul)
2023, Professor Feipeng Zhang, School of Finance and Economics, Xi’an Jiaotong University, Xi’an, China (27 Mar – 25 May)
2023, Mr Bo Pan, Biostatistician, Epidemiology Coordinating and Research (EPICORE) Centre, University of Alberta, Edmonton, Canada
2023, Dr Yafei Wang, Lecturer in Statistics, Department of Mathematical Sciences, University of Essex, Colchester, United Kingdom
11/2026: i-Risk Doctoral Focal Award, UKRI NERC (fully funded 3.5-year PhD studentship, stipend £21,805 p.a. plus UK-rate tuition fees; Lead supervisor). Project: Deep Extreme Value Learning for Landslide Tail Risk in a Changing Climate (IRISK-27-LU08). Co-supervisors: Lu Zhang, Monia Del Pinto (Loughborough), Derek Ma (Warwick), Alessandro Novellino (British Geological Survey).
11/2026: EPSRC EMERGE RehabTech Collaboration Fund Mobility Grant (£1,490, Co-I). Project: A Translational Scoping Study for Inclusive and Clinically Implementable AI-Enabled Remote Rehabilitation in Leicestershire. PI: Dr Claire Guo, Loughborough University. Funded by EPSRC through the EMERGE RehabTech PBIAA, administered by Nottingham Trent University.
11/2026: EPSRC EMERGE RehabTech Collaboration Fund Mobility Grant (£2,860, PI). Project: Co-designing Accessible Digital Rehabilitation Technologies to Improve Engagement and Reduce Health Inequalities Following Orthopaedic Surgery. Funded by EPSRC through the EMERGE RehabTech PBIAA, administered by Nottingham Trent University.
06/2026: London Mathematical Society, Scheme 4, Research in Pairs (£1,600, PI). Project: Support of collaborative research with Dr Bilel Bousselmi (Loughborough University and ESME Sudria Graduate School of Engineering). Grant period: 19 October 2026 – 18 June 2027.
06/2026: EPSRC Summer Vacation Internship (£7,000, PI). Intern: Ms Nayla Ruiz Salfity, Loughborough University.
01/2026: Darktrace-Loughborough PhD Studentship, AI and Cyber Security (£100,000, PI). Project: LLM-Powered Synergistic Framework for Dynamic Privacy Enhancement and Unknown Leakage Detection in Multi-Modal Medical Data.
06/2024: Google Cloud Research Credits, Google, United States ($5,000, PI).
03/2024: Networking Grants Round 1, The Academy of Medical Sciences, United Kingdom (£18,620, PI). Project: Exploring the Application of Large Language Models in Medical Image Analysis: Integrating Statistics to Ensure Fairness and Privacy Protection. This grant led to a workshop at the University of Alberta, Canada, on 21 August 2024 (https://sites.google.com/view/workshop-ai-medicalimaging/home).
10/2023: UK Research and Innovation (UKRI) Knowledge Transfer Partnerships (KTP) Fund (£198,550, Co-I). Project: Improving the Statistical Analysis of Brain Imaging Data to Generate More Accurate Descriptions of Brain Activity. Company partner: Innovision IP.
03/2023: Cyber Security Seedcorn Funding, Institute of Cyber Security for Society, University of Kent (£2,850, PI). Project: Federated Learning-based Quantile Regression Model for Credit Card Fraud Detection.
01/2023: UK Research and Innovation (UKRI) General Funds (£6,750, PI). Project: Expectile Threshold Autoregressive (TAR) Regression Model.
02/2022: Research and Innovation Fund, Division of Computing, Engineering and Mathematical Sciences (CEMS), University of Kent (£2,953, PI). Project: Federated Learning for Neuroimaging Data Analysis.