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Professor, Department of Statistics and Institute of Data Science, National Cheng Kung University
Professor, Department of Statistics and Institute of Data Science, National Cheng Kung University
Education: University of Minnesota -- Twin Cities
Education: University of Minnesota -- Twin Cities
Research: Bayesian Statistics, fMRI Data Analysis, Spatio-Temporal Models
Research: Bayesian Statistics, fMRI Data Analysis, Spatio-Temporal Models
Experience
Chair of Department of Statistics and Institute of Data Science, NCKU, Aug 2025 to present
Fulbright Scholar (Senior Research Award) at Department of Biostatistics, VUMC, Aug 2024 to July 2025
Director of Institutional Research Division Office of Research and Development, NCKU, Feb 2023 to Jul 2024
President of Banyan Garden Statistics and Education Foundation, Jan 2021 to Dec 2023
Secretary, International Society for Bayesian Analysis (IBSA), Easter Asia Chapter, Jan 2021 to present.
Associate Professor, Department of Statistics, NCKU Aug 2017 to July 2023
Assistant Professor, Department of Statistics, NCKU Aug 2012 to July 2017
Postdoctoral associate, Rochester Center for Brain Imaging (RCBI) at University of Rochester, Sep 2010 to July 2012
Selected Publications
1. Robust Bayesian cumulative probit linear mixed models for longitudinal ordinal data. Kuo-Jung Lee, Ray-Bing Chen, and Keunbaik Lee. Computational Statistics, May, 2024.
2. Multivariate Probit Linear Mixed Models for Multivariate Longitudinal Binary Data. Kuo-Jung Lee, Chanmin Kim, Jae Keun Yoo, and Keunbaik Lee. Statistics in Medicine, Online. February, 2024.3
3. Robust probit linear mixed models for longitudinal binary data. Kuo-Jung Lee, Chanmin Kim, Ray-Bing Chen, Keunbaik Lee. Biometrical Journal, 1307-1324, 2022
4. Variable selection in finite mixture of regression models with an unknown number of components. Kuo-Jung Lee., Chen Y-C., & Feldkircher M. Computational Statistics and Data Analysis, 158, June 2021, 107180
5. Determination of Correlations in Multivariate Longitudinal Data with Modified Cholesky and Hypersphere Decomposition using Bayesian Variable Selection Approach. Kuo-Jung Lee., Chen, R-B., & Lee KB. Statistics in Medicine, 978-997, 2021
6. Bayesian variable selection in a finite mixture of linear mixed-effects models. Kuo-Jung Lee. & Chen, R-B., 2019 September 2, Journal of Statistical Computation and Simulation. 89, 13, p. 2434-2453.
7. Of Needles and Haystacks: Revisiting Growth Determinants by Robust Bayesian Variable Selection. Kuo-Jung Lee & Chen, Y. C., 2018 June 1, Empirical Economics. 54, 4, p. 1517-1547 31 p
8. Spatial Bayesian hierarchical model with variable selection to fMRI data. Kuo-Jung Lee, Hsieh, S. & Wen, T., 2017 August, Spatial Statistics. 21, p. 96-113.
9. Bayesian variable selection for finite mixture model of linear regressions. Kuo-Jung Lee, Chen, R. B. & Wu, Y. N., 2016 March 1, Computational Statistics and Data Analysis. 95, p. 1-16.
10. Spatial Bayesian variable selection models on functional magnetic resonance imaging time-series data. Kuo-Jung Lee., Jones, G. L., Caffo, B. S. & Bassett, S. S., 2014 January 1, Bayesian Analysis. 9, 3, p. 699-732.
Teaching
Teaching
Summer, 2019 and 2020: Statistical Methods (English, IMBA)
Spring 2018: Calculus (Undergraduate) & Mathematical Statistics (Undergraduate)
Fall 2018: Calculus (Undergraduate) &Statistical Methods (Graduate)
Spring 2017: Calculus (Undergraduate) & Categorical Data analysis (Undergraduate)
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