Members

Current Students

MS students

1.  함수혁

2. 이문기

3. 박주성  
   
   
   

Undergraduate research students 

1. 이송아 (중앙대학교 응용통계학과) :                  

• Mar. 2024 - present

• PM 10 prediction using Extreme random forest

2. 박강비 (중앙대학교 식품공학/응용통계학과) :            

1. 1. 1. • Apr. 2024 - present

• Prediction of the success of bank telemarketing

Alumni

1.  안소영

1. • 2020년 2월 졸업

   • MA Thesis: Forecasting daily PM10 concentration in Seoul Jong-no District by using various statistical techniques.

   •  S An and Y. Lim (2020). Forecasting daily PM10 concentration in Seoul Jong-no District by using various statistical techniques. Journal of the Korean Data & Information Science Society, 31(1), 185–196.

   • 오송첨단의료산업진흥재단 재직 / 성균관대학교 삼성융합의과학원 박사과정

2.  이웅주

• • 2020년 2월 졸업

  • MA Thesis:  Robust Group Independent Component Analysis.

  • H Kim, YJ Lee and Y. Lim (2021). Robust Group Independent Component Analysis. The Korean Journal of Applied Statistics, 34(2), 135-147.

  • (재) 한국장기이식연구단 재직

3.  황석영

• 2020년 8월 졸업

• MA Thesis:  Comparison of ICA algorithms using EEG data.

• 우리자산운용 재직

       4. 진태훈

• 2020년 8월 졸업

• MA Thesis:  Classification of subway stations in Seoul using  k-centres Functional Clustering .

• VGEN 재직

5. 장은성

• • 2021년 2월 졸업

  • MA Thesis:  Classification via Principal Differential Analysis.

  • E Jang and Y. Lim (2021). Classification via Principal Differential Analysis. Communications for Statistical Applications and Methods, 28(2), 135-150.

  • University of Maryland, College Park 박사과정

6. 김예슬

• • 2021년 2월 졸업

  • MA Thesis:  Analysis of Particulate Matter via Geographically Weighted Principal Component Analysis. 

  • 대림건설 혁신학교부서 데이터분석팀 재직

      7.  안효정

• • 2021년 8월 졸업

  • MA Thesis:  Clustering load patterns recorded from Advanced Metering Infrastructure.

  • H, Ann and Y. Lim (2021).  Clustering load patterns recorded from advanced metering infrastructure.  The Korean Journal of Applied Statistics, 34(6), 969–977.

  • 데이터솔루션 재직

8. 강동현

• • 2022년 2월 졸업

  • MA Thesis:  Clustering Non-stationary Advanced Metering Infrastructure Data.

  • D. Kang and Y. Lim (2022). Clustering Non-stationary Advanced Metering Infrastructure Data. Communications for Statistical Applications and Methods,  29(2), 85-99.

  • 신한은행 재직

9. 강성진

• • 2022년 2월 졸업

  • MA Thesis:  Ensemble Mapper.

  • S. Kang and Y. Lim (2021). Ensemble Mapper.  Stat.  10, e405.

  • 현대오토에버 재직

10. 이상혁

• • 2022년 2월 졸업

  • MA Thesis:  Prediction of extreme PM2.5 concentrations via extreme quantile regression.

  •  Lee, S and Y. Lim (2022).  Prediction of extreme PM 2.5 concentrations via extreme quantile regression. Communications for Statistical Applications and Methods,  29(3), 319-331.

11. 이지선

• 2022년 2월 졸업

• MA Thesis: Clustering daily AMI data using the sequential clustering method.

• J. Lee and Y. Lim (2022).  Clustering daily AMI data using the two-step clustering method. Journal of the Korean Data & Information Science Society, 33(1), 153-166.

• 위데이터랩 재직 

12. 김수현

• 2022년 8월 졸업

• MA Thesis:  Zero-Inflated Poisson Mixture Model applied to two real data.  

• 서울대학교병원  융합의학기술원 융합의학과 박사과정

13. 김창우

• 2022년 8월 졸업

• MA Thesis:  Mapper applied to COVID 19 data.

• 서울 아산병원 연구원

14. 김현성

• 2023년 2월 졸업

• 서울대학교 통계학과 박사과정

     15. 임동경

• 2023년 2월 졸업

• MA Thesis:  Forecasting high levels of PM10 in Korea based on the principal expectile component regression.

• Lim, D., and Lim, Y. (2023). Forecasting high levels of PM10 in Korea based on the principal expectile component regression. The Korean Data & Information Science Society, 34(1), 157-166.

• KT스카이라이프 재직

16. 임형준

• 2023년 2월 졸업

• MA Thesis: Change points detection for nonstationary multivariate time-series.

• Lim H, and Lim. Y. (2023), Change points detection for nonstationary multivariate time series. Communications for Statistical Applications and Methods, 30(4), 369-388.

• LG CNS 재직

17. 최지은

• 2023년 2월 졸업

• MA Thesis:  Wavelet-based prediction method for ground temperature in South Korea.

• Choi, J., and Lim, Y. (2023). Wavelet-based prediction method for ground temperature in South Korea. The Korean Data & Information Science Society, 34(2), 279-289.

• 분당서울대병원 연구원

18. 이경서

• 2024년 2월 졸업

• MA Thesis:  Forecasting Korea’s GDP growth rate based on the dynamic factor model

• Lee, KS., and Lim, Y. (2024). Forecasting Korea’s GDP growth rate based on the dynamic factor model, The Korean Journal of Applied Statistics, In press.

• 코리아리서치인터네셔널 재직

19. 이정균

• 2024년 2월 졸업

• MA Thesis:  Aerosol optical depth prediction based on dimension reduction methods

• Lee, J., and Lim, Y. (2024). Aerosol optical depth prediction based on dimension reduction methods. Communications for Statistical Applications and Methods, In press.

• 한국평가데이터(KODATA) 재직, 신용리스크 컨설팅 직무