1998.3 육군사관학교 졸업 (공학사)
2006.3 미. 공군대학원 졸업 (운영분석 석사)
2011.8 고려대학교 대학원 졸업 (통계학 박사)
2006.3 - 2007.9 육군사관학교 수학과 강사
2007.9 - 2011.8 육군사관학교 수학과 전임강사
2011.8 - 2015.11. 육군사관학교 수학과 조교수
2015.11 ~ 현재 수학과 부교수
2014.1 - 2015.8. 수학과장
2015.9 - 2016.8. 미 남플로리다 주립대(USF) 방문교수
2016.8 - 2017.11 수학과장
2017.11 ~ 2018.12 교수학습개발원 기획총괄장교
2018.12 ~ 2019.12 평가관리실 선발과장
2019.12 ~ 현재 수학과장

1학년 미분적분학, 선형대수학
2학년 통계의 이해
3학년 수리통계학
4학년 통계적 방법론

Computer Intensive Methods, Machine Learning, Bootstrap

Excel과 함께하는 통계학의 이해와 활용 (교우사, 2011)
R과 함께하는 판별분석과 로지스틱 회귀분석 (교우사, 2013)
Excel과 R을 이용한 통계학의 이해와 활용 (교우사, 2015)
R을 이용한 통계분석 방법론의 이해와 활용 (교우사, 2017)

연구과제
- 커널에 기반한 비선형 분위수 함수의 강건한 추정에 관한 연구 (한국연구재단, 2013. 6 ~ 2014. 5)
- 비교차 다중 분위수 회귀나무모형의 강건한 추정에 관한 연구 (한국연구재단, 2015. 7 ~ 현재)

연구보고서
- 다변량 판별분석과 로지스틱 회귀분석을 이용한 합격/불합격 예측모형 개발 (화랑대연구소, 2012)
- 벌칙함수를 이용한 회귀 모형의 2단계 추정법 개발과 활용에 관한 연구 (화랑대 연구소, 2013)
- 불균형 자료의 분류분석을 위한 서포트 벡터 머신에 관한 연구 (화랑대 연구소, 2014)
- 샘플링 기법을 적용한 로지스틱 회귀분석의 비교 연구 (화랑대 연구소, 2015)

*:Corresponding Author

Kim, J., Cho, H., Bang, S.* (2019). Unified noncrossing multiple quantile regressions tree. Journal of Computational and Graphical Statistics. 28(2), 454-465.

Kang, J., Shin, S., Park, J., and Bang, S.* (2018). Hierarchically penalized quantile regression with multiple responses. Journal of the Korean Statistical Society. 47(4), 471-481.

Bang, S. (2018). A comparison study of penalized multivariate quantile regression. Journal of the Korean Data Analysis Society. 20(30), 1167-1179.

Kim, J., Bang, S., and Kwon, O.* (2017). Analysis of scientific military training data using zero-inflated and Hurdle regression. Journal of the Korean Data & Information Science Society. 28(6), 1511-1520.

Park, J. and Bang, S.* (2017). Electrical load forecasting using time series model. Journal of the Korean Data Analysis Society. 19(6), 3009-2018.

Jhun, M., Kang, J., and Bang, S.* (2017). Selection of bandwidth for local linear composite quantile regression smoothing. The Korean Journal of Applied Statistics. 30(5), 733-745.

Kim, J., Cho, H., Bang, S.* (2017). Multivariate quantile regression tree. Journal of the Korean Data & Information Science Society. 28(3), 533-545.

Bang, S., Kang, J., Jhun, M., and Kim, E. (2017). Hierarchically penalized support vector machine with grouped variables. International Journal of Machine Learning and Cybernetics. 8(4), 1211-1221.

Kang, J., Park, J., and Bang, S.* (2017). Hierarchically penalized sparse principal component analysis. The Korean Journal of Applied Statistics, 30(1), 135-145.

Bang, S., Eo, S., Jhun, M., and Cho, H. (2017). Composite kernel quantile regression. Communications in Statistics-Simulation and Computation. 46(3), 2228-2240.

Kim, J., Cho, H., and Bang, S.* (2016). Penalized quantile regression tree. The Korean Journal of Applied Statistics. 29(7), 1361-1371.

Bang, S. And Shin, S.J. (2016). A comparison study of multiple linear quantile regression using non-crossing constraints. The Korean Journal of Applied Statistics, 29(5), 773-786.

Kim, E., Jhun, M., and Bang, S.* (2016). Hierarchically penalized support vector machine for the classification of imbalanced data with grouped variables. The Korean Journal of Applied Statistics, 29(5), 961-975.

Hwang, J., Park, J. and Bang, S.* (2016). Estimation Method for Accuracy of Fire Using James-Stein Estimator. Journal of the Korean Data Analysis Society. 18(1), 141-150.

Bang, S. Cho, H., and Jhun, M. (2016). Simultaneous estimation for non-crossing multiple quantile regression with right censored data. Statistics and Computing, 26(1-2), 131-147.

Bang, S., Eo, S., Cho, Y., Jhun, M., and Cho, H. (2016). Non-crossing weighted kernel quantile regression with right censored data. Lifetime Analysis. 22(1), 100-121.

Bang, S., Cho, H., and Jhun, M. (2016). Adaptive lasso penalized censored composite quantile regression. Internatioinal Journal of Data Mining and Bioinformatics. 15(1), 22-46.

Kang, J., Bang, S., and Jhun, M. (2016). Hierarchically penalized quantile regression. Journal of Statistical Computation and Simulation. 86(2), 340-356.

Park, J. and Bang, S.* (2015). Logistic regression with sampling techniques for the classification of Imbalanced data. Journal of the Korean Analysis Society. 17(4), 1877-1888.

Kim, E., Jhun, M., and Bang, S.* (2015). Weighted 1-norm support vector machine for the classification of highly imbalanced data. The Korean Journal of Applied Statistics. 28(1), 9-21.

Bang, S. and Jhun, M. (2014). Weighted support vector machine using K-means clustering. Communications in Statistics-Simulation and Computation. 43(10), 2307-2324.

Kang, J., Bang, S., and Jhun, M. (2014). Simultaneous confidence intervals for the ratios of the marginal means of multivariate Poisson distribution. Communications in Statistics - Simulation and Computation, 43(7), 1783-1796.

Bae, H., Oh, K., and Bang, S. (2014). A study of the pass/fail classification model for the entrance examination in Korea Military Academy using linear discriminant analysis, 한국군사학논집. 70(1), 191-202.

Bang, S. and Jhun, M. (2014). Adaptive sup-norm regularized simultaneous multiple quantiles regression. Statistics: A Journal of Theoretical and Applied Statistics. 48(1), 17-33.

Bang, S., Jhun, M., and Cho, H. (2013). Stepwise estimation for multiple non-crossing quantile regression using kernel constraints. The Korean Journal of Applied Statistics. 26(6), 915-922.

Bang, S. (2013). Median Based Permutation Tests for Location Problems. 화랑대 논문집. 6(1), 75-84

Bang, S. and Jhun, M. (2013). Two-stage penalized composite quantile regression with grouoed variables. Communications for Statistical Applications and Methods. 20(4), 259-270.

Bang, S. and Jhun, M. (2012). On the use of adaptive weights for the F infinite norm support vector machine. The Korean Jounal of Applied Statistcs. 25(5), 829-835.

Bang, S., Lee, S., and Bae, H. (2012). A study on Gaussian mixture clustering for missing value imputation. 화랑대논문집. 5(2), 61-71.

Seo, K., Bang, S., and Jhun, M. (2012). Bootstrapping composite quantile regression. The Korean Journal of Applied Statistics. 25(2), 341-350.

Bang, S. and Jhun, M. (2012). Simultaneous estimation and foactor selection in quantile regression via adaptive sup-norm regularization. Computational Statistics and Data Analysis. 56(2), 813-826.

Park, S., Bang, S., and Jhun, M. (2011). On the use of sequential adaptive nearest neighbors for missing value imputations. The Korean Journal of Applied Statistics. 24(6), 1249-1257.

Bang, S. (2011). A study on variable selection in quantile regression models. Ph.D. Thesis, Korea University, Seoul.

Maeng, J., Bang, S., and Jhun, M. (2010). On the use of modified adaptive nearest neighbors for classification. The Korean Jounal of Applied Statistics. 24(6), 1093-1102.

Bang, S., Koo, J., and Jhun, M. (2010). Support vector machine using k-spatial medians clustering and recovery process. Communications in Statistics-Simulation and Computation. 39(7), 1422-1434.

Bang, S., Yoon, B., and Hwang, K.(2007). A logistics support model for humanitarian assistance operations. 육사논문집. 63(3), 411-423.

Lee, S., Hwang, K., and Bang, S. (2007). A study on chow groups of complete regular local rings of dimension 5. 육사논문집. 63(3), 203-210.

Bang, S. and Lee, S. (2007). Coalition mission-unit grouping model. 육사논문집. 63(1), 255-268.

Bang, S. (2006). Coalition modeling in humanitarian assistance operations. Master Thesis. Air Force Institute of Technology, Ohio.