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Research area(s)

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 small 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;
  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.

Grants

Resaerch Methods
Funder: National Institute for Health Research
Duration: -

Research project(s) and grant(s)

Current Grants as PI:

The UK Office for National Statistics (ONS) awarded funds in its first ever open call for research in economic measurement to him for a project entitled New regression models for the analysis of wellbeing and income distribution (https://www.brunel.ac.uk/research/Projects/New-regression-models-for-the-analysis-of-well-being-and-income-distribution)  (04/2019---03/2020), £5000.00.

EPSRC Case Studentship: Data Analytics for Risk Based Decision Making in Asset Integrity Management (01/01/2018—30/09/2020), £80,670.

National Institute for Health Research (NIHR): NIHR Research Methods Opportunity Funding Scheme £70,517 (2010—2011) and £68,883 (2014-2015).

NSIRC scholarship funded by TWI (Cambridge) for supporting  three  PhD study on Statistical analysis and modelling of corrosion data:  £98,890 (2014—2020).