Heeju Lim
Ph.D. in Statistics
I received my Ph.D. in Statistics from the University of Connecticut in 2026 under the supervision of Professor Victor Hugo Lachos. I earned my M.S. in Statistics from Korea University in 2017 under the supervision of Professor Yousung Park, and my B.S. in Statistics from Sejong University in 2015. I worked as an undergraduate research assistant and later as a full-time research assistant with Professor Seungyeoun Lee at Sejong University.
I also gained practical experience as a data analyst and data scientist at DataSolution(데이타솔루션), the National Tax Service of Korea(국세청 국세통계센터), and Korea University COSS(고려대학교 혁신융합대학사업), where I applied statistical and data science methods to real-world problems.
My research interests include sample selection models, missing data mechanisms, mixture modeling under heavy-tailed distributions, and multivariate statistical modeling. I have developed R packages including Heckmanstan and mvHeckman for statistical modeling.
I also completed a Big Data Specialist training program and hold an Oracle Certified Professional (OCP) certification, with experience in database management and large-scale data handling. In addition, I served as a webmaster at the University of Connecticut for three years, where I contributed to web development and conference organization activities.
Research Themes
Sample Selection & Missing Data
Bayesian Analysis
Mixture Modeling
Causal inference
Education
🎓 Ph.D. in Statistics
University of Connecticut · 2019–2021, 2023–2026
Advisor: Victor Hugo Lachos
🎓 M.S. in Statistics
Korea University · 2015 – 2017
Advisor: Yousung Park
🎓 B.S. in Statistics
Sejong University · 2010 – 2015
Advisor: Seungyeoun Lee
Featured Publications
Bayesian analysis of heavy-tailed Heckman selection models using Hamiltonian Monte Carlo
Heeju Lim, Victor E. Lachos, Victor H. Lachos
Computational Statistics · February 2026
Heckman Selection-Contaminated Normal Model
Heeju Lim, Jose Ordonez, Antonio Punzo, Victor H. Lachos
Journal of Computational and Graphical Statistics · February 2026
Publications
2026
Multiple Heckman Selection Model (preprint)
Heeju Lim, Carlos A. R. Diniz, Ofer Harel, Victor H. Lachos Preprint· 2026
Preprint
2019
Review of Statistical Methods for Survival Analysis Using Genomic Data
Seungyeoun Lee, Heeju Lim Genomics & Informatics· 2019
Article
Presentations
Heckman Selection Contaminated Normal Model
Contributed Session | ENAR 2025 Spring Meeting. New Orleans, USA, March 2025
Poster Winner | The 7th Stat4Onc Annual Symposium. Connecticut, USA, May 2024
Student Session | The 37th New England Statistics Symposium. Connecticut, USA, May 2024
Bayesian Analysis of Flexible Heckman Selection Models
Invited Session | 2025 ICSA Applied Statistics Symposium. Connecticut, USA, June 2025
Poster | The 38th New England Statistics Symposium. Connecticut, USA, May 2025
Poster | DahShu Data Science Symposium. Connecticut, USA, October 2025
Study on Predictive Survival Models using Machine Learning
- Poster | The Korean Statistical Society conference. Chuncheon, South Korea, May 2019
Teaching Experience
Discussion Instructor
Elementary Concepts of Statistics (STAT 1000Q)
Fall 2024 · Spring 2025 · Fall 2025
University of Connecticut
Teaching Assistant
- Applied Spatio-Temporal Statistics (Fall 2025)
- Linear Models I (Fall 2024)
- Introduction to Mathematical Statistics II (Spring 2021)
- Introduction to Mathematical Statistics I (Fall 2020)
Sejong University
Teaching Assistant
- Bayesian Statistics (Fall 2018)
- Mathematical Statistics II (Fall 2014)
Korea University
Teaching Assistant
- Introduction to Database (SQL) (Fall 2015)
- Introduction to C Programming (Spring 2015)