Dr Lee How Chinh is a quantitative researcher whose work integrates advanced statistical modelling, machine learning, and econometrics to address real-world problems in finance, economics, and business analytics. His research focuses on developing robust and interpretable analytical methods for high-dimensional and heterogeneous data, where traditional modelling approaches are often inadequate.

A key theme in his work is the integration of methodological innovation with practical decision-making. He designs data-driven frameworks that translate complex analytical results into actionable insights for industry and public-sector stakeholders, particularly in areas such as financial risk, market behaviour, and evidence-based policy.

Dr How Chinh actively supervises PhD and postgraduate research that is methodologically rigorous and application-driven. He encourages students to engage deeply with data, question standard assumptions, and develop transparent, reproducible analytical solutions that balance statistical validity with real-world usability.

Professional Training

Dr How Chinh is a HRD Corp certified trainer and SAS accredited trainer. He designs and delivers specialised training in advanced analytics, econometrics, and SAS modelling for public-sector agencies and industry partners. His workshops emphasise the integration of rigorous quantitative methods with practical decision-making, enabling participants to translate complex analytical results into reliable and actionable insights.

His training engagements typically cover:

• Applied econometrics and high-dimensional modelling
• Machine learning for business analytics
• SAS programming for analytical and reproducible workflows
• Model interpretation, validation, and robustness
• Data literacy and data-driven decision frameworks

Dr How Chinh has worked closely with companies, financial institutions, and government bodies to strengthen analytical capability and support evidence-based decision-making.

• ETW3482 Data Mining And Predictive Modelling
• ETM3800 Text Analytics for Business
• ETM5800 Text Analytics for Business

• Applied predictive modelling in finance, marketing, and risk
• Big data analytics and high-dimensional econometrics
• Machine learning for heterogeneous and complex datasets
• Financial and economic time-series modelling
• Text and image analytics for social and economic insights
• Robust and interpretable statistical modelling
• Data-driven decision support for industry and public sector

• UTAR DataFest 2021, Chief Judge
• The 6th International Conference on Soft Computing in Data Science (SCDS2021), Technical Reviewer. 
• The 16th IMT-GT International Conference on Mathematics, Statistics and Its Applications (ICMSA 2020), Committee Member and Technical Reviewer.
• The 5th International Conference on Soft Computing in Data Science (SCDS2019), Technical Reviewer.
• 2019 Innovate Malaysia Design Challenge (SAS Track), Judge
• 2018 Innovate Malaysia Design Challenge (SAS Track), Judge
• 2017 Innovate Sarawak Design Challenge (Big Data Track), Judge
• The 6th IMT-GT International Conference on Mathematics, Statistics, and Its Applications (ICMSA 2010), Committee Member