Statistical Learning and Data Mining
Big Data Analysis
B.S. Department of Computer Science and Statistics, Seoul National University
M.S. Department of Statistics, Seoul National University
Ph.D. Department of Statistics, Ohio State University
1997 – 1999
Researcher, National Institutes of Health, U.S.A.
1999 – 2001
Assistant professor, Department of Information Statistics, Hankuk University of Foreign Studies
2001 – 2004
Assistant professor, Department of Statistics, Ewha Womans University
2004 – 2011
Assistant professor, Department of Statistics Seoul National University
Professor, Department of Statistics Seoul National University
Kim, Y. (1999). Nonparametric Bayesian estimators for counting processes, Annals of Statistics, 27, 562-588.
Kim, Y. and Lee, J. (2001) On posterior consistency of survival models. Annals of Statistics, 29,666-686.
Kim, Y. and Lee, J. (2003) Bayesian analysis of proportional hazard models. Annals of Statistics, 31, 493-511.
Kim, Y. and Lee, J. (2003). Bayesian bootstrap for the Cox’s proportional hazard model. Annals of Statistics. 31, 1905-1922.
Kim, Yongdai and Lee, Jaeyong (2004) A Bernstein von-Mises theorem in the nonparametric right-censored model, Annals of Statistics, 32, 1492-1512.
Park, Eunsik and Kim, Yongdai (2004) Analysis of longitudinal data in case control studies, Biometrika, 91, 321-330.
Kim, Yongdai (2006) The Bernstien -von Mises theorem for the proportional hazard model. Annals of Statistics, 34, 1678-1700.
Pillar, Ramani, Kim, Yongdai and Lee, Hakbae (2008) On casting random effects model in a survival framework. JRSS-B, 70, 629-642.
Kim, Yongdai, Choi, Hosik and Oh, Heeseok (2008). SCAD on high
dimensions. Journal of the American Statistical Association, 103, 1655-1673.
Kim, Yongdai and Kwon, Sunghoon (2012). Global optimality of nonconvex penalized estimators, Biometrika, 99(2) 315-325.
Kim, Yongdai, James, Lancelot and Weissbach, Rafael. (2012). Bayesian analysis of a multi-state event history data: Beta-Dirichlet process, Biometrika 99(1), 127-140.
Wang, Lan, Kim, Yongdai and Li, Runze (2013). Calibrating Non-convex Penalized Regression in Ultra-high Dimension. Accepted by Annals of Statistics
Best Paper Award
2002 IEEE International Conference on Data Mining. Maebashi, JAPAN Title: Convex Hull Ensemble Machine
2003 우수연구 30선
Title : 차세대 데이터마이닝 알고리즘
Title : 차세대 데이터마이닝 알고리즘
US Air Force Research Fund: 2002.9 -2003.8
Title: Convex Hull Ensemble Machine: Theory and Applications
US Air Force Research Fund: 2003.9 – 2004.8
Title: Learning with Data Adaptive Features
2007 서울대학교 연구력 향상 공로교수
2013 품질경영학회 통계부문 코오롱 우수 논문상