심주용                                                   

<학력>

​서강대학교 화학공학과(공학사)

Northeastern Illinois University 수학과(이학석사)

University of Illinois at Urbana-Champaign​ 통계학과(이학석사, 박사과정수료)

경북대학교 통계학과(이학박사)

​​

<전공 및 연구분야>

다변량통계학, 기계학습, 패턴인식, 데이터마이닝, 의학통계학, 생물정보학, 보험수리 등

​

​<경력>

쥬리아화장품 연구실 근무

​삼성반도체통신 근무

​E & K International 근무

​University of Illinois 통계학과 연구조교

​경북대학교 통계학과 시간강사

​대구가톨릭대학교 정보통계학과 겸임교수

​(주)동부그린 측정부장

​선호플랜트ENG 관리이사

​인제대학교 통계학과 겸임교수

<수상경력>

<연구개발 경력>

<논문 실적 목록>​

1. Variable selection in L1 penalized censored regression. Journal of the Korean Data & Information 

   Science Society, 22, 951-959. 2011.

2. Semiparametric mixed-effect least squares support vector machine for analyzing pharmacokinetic 

   and pharmacodynamic data. Neurocomputing, 74, 3412-3419.  2011.

3. Variance function estimation using SVM and Jack-Knife method. Journal of the Korean Data 

   Anaysis Society. 13, 2243-2251. 2011.

4. Transductive kernel logistic regression for semisupervised classification in Bioscience. 

   Quantitative Bio-Scinece, 30, 123-127. 2011.

5. Semiparametric kernel logistic regression with longitudinal data. Journal of the Korean Data & 

   Information Science Society, 23, 385-392. 2012.

6. Two-step LS-SVR for censored data. Journal of the Korean Data & Information Science Society, 

   23, 393-401. 2012.

7. 생존자료분석을 위한 혼합효과 최소제곱 서포트벡터기계, Journal of the Korean  Data & Information 

   Science Society, 23,739-748. 2012.

8. 소지역 추정을 위한 M-분위수 커널회귀. Journal of the Korean Data & Information Science Society, 

   23, 749-756. 2012.

9. Estimating multiplicative competitive interaction model using kernel machine technique. Journal 

   of the Korean Data & Information Science Society, 23, 825-832. 2012.

10. 단조 서포트벡터기계를 이용한 Kaplan-Meier 생존함수의 평활. Journal of the Korean Data & 

   Information Science Society, 23, 1045-1054. 2012.

11. Kernel Poisson regression for mixed input variables. Journal of the Korean Data & Information 

   Science Society, 23, 1231-1239. 2012.

12. Estimation of VaR using semiparametric SVQR. Computational Statistics, 27, 685-700. 2012.

13. Variable Selection in censored kernel regression. Journal of the Korean Data & Information 

   Science Society, 24, 201-209. 2013.

14. GACV for partially linear SVR. Journal of the Korean Data & Information Science Society, 24, 391-

   399. 2013.

15. Expected shortfall estimation using kernel machines. Journal of the Korean Data & Information 

   Science Society, 24, 625-636. 2013.

16. Partially linear Support vector quantile regression using asymmetric e-insensitive loss function. 

   Journal of the Korean Data Anaysis Society, 15, 1767-1776. 2013.

17. 소지역 실업률의 패널추정을 위한 일반화커널추정방정식. Journal of the Korean  Data & Information 

   Science Society, 24, 1199-1210. 2013.

18. Semiparametric spatial effects kernel minimum squared error model for predicting housing sales 

   prices. Neurocomputing, 124, 81-88. 2014.

19. Transcription factor binding site identification and gene classification via fusion of supervised 

   weighted discrete kernel clustering and support vector machine. Journal of Applied Statistics, 41, 

   573-581. 2014.

20. Quantile regression with errors in variables. Journal of the Korean Data & Information Science 

   Society, 25, 439-446. 2014.

21. A transductive least squares support vector machine with the difference convex algorithm.  

   Journal of the Korean Data & Information Science Society, 25, 455-464. 2014.

22. Sparse SVQR for detecting differently expressed genes. Quantitative Bio-  Science, 33, 5-20. 

   2014.

23. SVQR Ensemble with Bagging, Journal of the Korean Data & Information Science Society, 29, 

   677-684, 2017

24. Kernel-based random effect time-varying coefficient model for longitudinal data. 

   Neurocomputing, 267, 500-507, 2017.

25. Kernel-based orthogonal quantile regression model. Model Assisted Statistics and Applications, 

   12, 217-226, 2017.

26. Semivarying coefficient least-squares support vector regression for analyzing high-dimensional 

   gene-environmental data. Journal of Applied Statistics, 1-12, 2017. 

27. Kernel-based geographically and temporally weighted autoregressive model for house 

   price estimation, PLoSONE, 13, 10, 1-16, 2018.

28. Kernel-based spatial error model for analyzing spatial panel data, Model Assisted Statistics and

   Applications 15, 239-248, 2020