Korea University Department of Statistics

Ph.D. in Statistics, 2010, Ohio State University, Columbus, OH, U.S.A.

M.S. in Statistics, 2006, Ohio State University, Columbus, OH, U.S.A.

March 2018 - current: Associate Professor, Korea University, Seoul, South Korea

Feb. 2017– current, Assistant Professor, Korea University, Seoul, South Korea

Feb. 2016 – Feb. 2017, Senior Lecturer, University of Waikato, Hamilton, New Zealand

July 2013 – Jan. 2016, Lecturer, University of Waikato, Hamilton, New Zealand

June 2010 – June 2013, Postdoctoral Fellow, University of Texas MD Anderson Cancer Center, Houston, TX, U.S.A.

 International Academic Journals

• ● Jung, Y. (2019) Nonlinear Regression Models for Heterogeneous Data with Massive Outliers, Journal of Applied Statistics (In Press)
• ● Jung, Y. and Hu, J. (2019) Review: Reversed Low-rank ANOVA Model for Transforming High Dimensional Genetic Data into Low Dimension, Journal of the Korea Statistical Society (In Press)

• ● Jung, Y., Zhang, H., and Hu, J. (2019) Transformed Low-rank ANOVA Models for High-dimensional Variable Selection, Statistical Methods in Medical Research (In Press)
• ● De Mello Costa, M.F., Ronchi, F.A., Jung, Y., Ivanow, A., Brage, J.V., Ramos. M.T., Casarini, D.E., and Slocombe, R.F. (2018) ACE Activity Post-race is Influenced by Furosemide Administration, Comparative Exercise Physiology , 14 (2), 119 - 125.

• Jung, Y. (2018) Multiple Predicting K-fold Cross-validation for Model Selection, Journal of Nonparametric Statistics , 30 (1), 197 - 215.

• Jung, Y. (2017) Shrinkage Estimation of Proportion via Logit Penalty, Communications in Statistics - Theory and Methods, 46 (5), 2447 – 2453.

• Hardie, C., Jung, Y., and Jameson, M. (2016) Effect of Statin and Aspirin Use on Toxicity and Pathological Complete Response Rate of Neo-adjuvant Chemoradiation for Rectal Cancer. Asia-Pacific Journal of Clinical Oncology, 12, 167 – 173.

• Jung, Y., Lee, S. P., and Hu, J. (2016) Robust Regression for Highly Corrupted Response by Shifting Outliers. Statistical Modelling, 16 (1), 1 – 23.

• Jung, Y. (2016) Efficient Tuning Parameter Selection by Cross-Validated Score in High Dimensional Models. International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering, 10 (1), 19 – 25.

• Jung, Y., and Hu, J. (2015) A K-fold Averaging Cross-validation Procedure. Journal of Nonparametric Statistics, 27 (2), 167 – 179. [Journal of Nonparametric Statistics Best Paper Award 2015]

• Jung, Y., Lee, Y., and MacEachern, S. N. (2015) Efficient Quantile Regression for Heteroscedastic Models. Journal of Statistical Computation and Simulation, 85 (13), 2548 – 2568.

• Jung, Y., Hu, J., and Huang, J. (2014) Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA. Journal of the American Statistical Association, 109 (508), 1355 – 1367.

• Yoo, J., Kim, J., Ro, S., Jung, Y., Jung, S., Choo, S., Lee, J., and Chung, C. (2014) Impact of concomitant surgical atrial fibrillation ablation in patients undergoing aortic valve replacement. Circulation Journal, 78 (6), 1364 – 1371.

• Lester, J., Wessels, A., and Jung, Y. (2014) Oncology Nurses' Knowledge of Survivorship Care Planning: The Need for Education. Oncology Nursing Forum, 41 (2), E35 – E43.

• Lee, Y., MacEachern, S. N., and Jung, Y. (2012) Regularization of Case-Specific Parameters for Robustness and Efficiency. Statistical Science, 27, 350 – 372.

• Lee, S., Lee I., Jung, Y., McConkey, D., and Czerniak, B. (2012) In-Frame cDNA library combined with protein complementation assay identifies ARL11-binding partners. PLoS ONE, 7(12): e52290.

 International Conference Proceedings

• Jung, Y., and MacEachern, S. N. (2016) Efficient Model Selection in Linear and Non- linear Quantile Regression by Cross-validation. Proceedings of International Conference on Computational and Statistical Sciences 2016, Paris, France.

Technical Reports

• Jung, Y., MacEachern, S. N., and Lee, Y. (2010) Window Width Selection for L2 Adjusted Quantile Regression. Technical Report No. 835, Department of Statistics, The Ohio State University.

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