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Lee Chinh is a Senior Lecturer (Practice) in the Department of Econometrics and Business Statistics at Monash University Malaysia. His research focuses on advanced big data analytics, machine learning, and the complex methodologies used for analyzing heterogeneous, high-dimensional data, which conventional statistical approaches struggle to address. Lee centers his work on developing and applying statistical and econometric methodologies for large-scale data analysis, including survey data, financial time series, unstructured text, and image data. His research emphasizes methodological innovation with a particular focus on model robustness and interpretability, tackling real-world data challenges such as heterogeneity, measurement error, mixed data frequencies, and unbalanced data structures. He actively supervises PhD candidates in method-driven analytical projects, especially those that advance statistical machine learning techniques with significant relevance to policy, finance, and industry. Lee collaborates with public sector partners to translate advanced analytics into actionable insights for decision-support systems.
Monash University Malaysia • Malaysia
Lee teaches courses in Econometrics and Business Statistics, focusing on data mining and predictive modeling.
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