Keming Yu

  • Professor in Statistics - Brunel University London

Research interests

Based on mathematical theory and data analysis methods, my research aims to explore statistical methods, models and optimal algorithms to deal with challenges in:

  1. Modelling the relationship or dependency as well as prediction among variables with Big or Small data sizes via regression models and classification, such as quantile regression models (nonparametric quantile regression and Bayesian quantile regression) and machine learning methods (regression tree, random forest);
  2. Statistical analysis of lifestyle interventions and economic evaluation for preventing Obesity, Asthma and other health issues;
  3. Risk assessment in financial econometrics and Exceedance probability of extreme events such as pollution, flooding;
  4. Statistical reliability analysis of smart manufacturing and renewable energy, such as corrosion data analysis in pipeline;
  5. Uncertainty quantification via Bayesian inference and dynamic process modelling.