Alex Gibberd

Dr Alex Gibberd is a Senior Lecturer (equivalent to Associate Professor) in Statistics within the School of Mathematical Sciences at Lancaster University. He has been a faculty member since 2018, following postdoctoral research at Imperial College London and a PhD in Statistics from University College London (UCL) in 2017. He also holds an MPhys in Astrophysics from the University of St Andrews (2012).

Education:

• PhD in Statistics, University College London (2017)
• MPhys in Astrophysics, University of St Andrews (2012)

Research Interests:

Dr Gibberd's research focuses on high-dimensional time-series analysis, with methodological contributions in statistical modeling under non-stationarity and high-dimensionality. His work spans both theoretical developments and practical applications, particularly in neuroscience and finance. Key areas include:

• Sparse dynamic factor models and regularized estimation techniques
• Spectral analysis and locally-stationary wavelet models
• Optimization algorithms for model selection in high-dimensional settings
• Applications in brain connectivity analysis and economic forecasting

Research Themes:

His recent publications demonstrate a strong focus on developing interpretable statistical methods for complex systems. These include advances in principal component analysis with joint rank and covariance estimation, sparse dynamic factor models, and regularized spectral estimation for high-dimensional point processes. The applications range from neural connectivity modeling to energy efficiency policy analysis.

Grants & Funding:

• Research in Paris Grant (2024)
• Support of Collaborative Research with Dr S. Roy at University of Bath (2021)
• Model Selection for High-Dimensional Temporal Disaggregation in Official Statistics (2021-2023)
• Reducing End Use Energy Demand in Commercial Settings Through Digital Innovation (2021-2025)
• Wavelet Methods for Dependency Analysis in Multivariate Time Series (2020)
• STOR-i: Information Fusion for Non-homogeneous Panel and Time-series Data (2019-2025)

PhD Supervision & Students:

Dr Gibberd supervises PhD students at the intersection of high-dimensional statistics and time-series analysis. Current students include Carla Pinkney (STOR-i CDT), Ziyan Zhao, and Kai Zheng (Centre for Marketing Analytics & Forecasting).

Research Affiliations:

• STOR-i Centre for Doctoral Training
• Centre for Marketing Analytics & Forecasting
• Changepoints and Time Series Research Group
• Data Science Institute - Foundations
• Social and Economic Statistics Group