|Name : Jung, Yoonsuh (정 윤 서)|
|Position : Associate Professor|
|TEL : 02-3290-2249|
|E-mail : firstname.lastname@example.org|
|Office : 525 Woodang Hall|
|Research Interests : High dimensional model, Quantile Regression, Variable Selection, Robust 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.B.S. in Statistics, 2003, Korea University, Seoul, Korea
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., Zhang, H., and Hu, J. (2018) Transformed Low-rank ANOVA Models for High-dimensional Variable Selection, Statistial Methods in Medical Research (Accepted)
• 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.
• 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.