黑料不打烊

Research Areas

Quantitative & Modelling

Research Interests:

Prof. Hwang鈥檚 research program is generally devoted to the development and application of quantitative methods to address diverse issues in psychology and various other fields. His recent interests include the development of data integration tools for high-dimensional data collected from multiple sources; the development of a statistical methodology for investigating associations among genetic, brain, and behavioural/cognitive phenotypes; and the development and application of predictive models or machine learning algorithms for predicting behavioural and cognitive outcomes using genetic, physiological, and psychological data.

Selected References

Lee, S., Choi, S., Kim, Y. J., Kim, B.-J., T2D-Genes Consortium, Hwang, H., & Park, T. (2016). Pathway-based approach using hierarchical components of collapsed rare variants. Bioinformatics, 32, i586-i594.

Romdhani, H., Hwang, H., Paradis, G., Roy-Gagnon, M.-H., & Labbe, A. (2015). Pathway-based association study of multiple candidate genes and multiple traits using structural equation models. Genetic Epidemiology, 39, 101-113.

Hwang, H., Suk, H. W., Takane, Y., Lee, J.-H., & Lim, J. (2015). Generalized functional extended redundancy analysis. Psychometrika, 80, 101-125.

Hwang, H., & Takane, Y. (2014). Generalized structured component analysis: A component-based approach to structural equation modeling. Boca Raton, FL: Chapman & Hall/CRC Press.

Hwang, H., Jung, K., Takane, Y., & Woodward, T. Functional multiple-set canonical correlation analysis (2012). Psychometrika, 77, 48-64.