CV

Education

M.S. in Statistics Feb 2026
Yonsei University, Seoul, Korea
GPA: 4.3/4.3 (4.0/4.0)

B.S. in Electrical and Electronic Engineering Feb 2023
Double Major: Applied Statistics
Yonsei University, Seoul, Korea
GPA: 4.02/4.3 (3.85/4.0 using 0.3-step, 3.86/4.0 using 0.33-step)

Research Experience

Master's Research (GitHub repo) (pdf) Aug 2024 – Jun 2025
Statistics and Data Science, Yonsei University

• Analyzed regularized LDA in the HDLSS regime via random matrix theory
• Derived closed-form MDP limit under identity covariance, explaining the peak error near aspect ratio p/n = 1
• Developed a numerically stable pipeline to compute limiting misclassification error and map optimal ridge parameter over (γ, ρ)
• Advisor: Prof. Yongho Jeon

Basic Research Lab Jan 2024 – Dec 2024
Statistics and Data Science, Yonsei University

• Covered theoretical statistics topics and applications in machine learning and deep learning.
• Participated in a weekly paper-reading and presentation seminar for graduate students.
• Presented: “Surprises in High-Dimensional Ridgeless Least Squares Interpolation” (Hastie et al., 2022).

EE Capstone Project (GitHub repo) (pdf) Jun 2022 – Dec 2022
Electrical and Electronic Engineering, Yonsei University

• Conducted research on how to match face picture with masked one
• Used methods such as cosine similarity and KL divergence
• Implemented corresponding codes using PyTorch
• Advisor: Prof. Andrew Beng Jin Teoh

Awards & Scholarships

University Designated Scholarship (Truth), Yonsei University Feb 2022

High Honors Award, Yonsei University Feb 2020

University Designated Scholarship (Truth), Yonsei University Aug 2019

University Designated Scholarship (Truth), Yonsei University Feb 2019

Honors Award, Yonsei University Feb 2019

Teaching Experience

Teaching Assistant, Mathematical Statistics (1) Sep 2025 – Dec 2025

Teaching Assistant, Regression Analysis Mar 2025 – Jun 2025

Teaching Assistant, Mathematical Statistics (1) Sep 2024 – Dec 2024

Teaching Assistant, Regression Analysis Mar 2024 – Jun 2024

Teaching Assistant, Regression Analysis Sep 2023 – Dec 2023

Teaching Assistant, Regression Analysis Mar 2023 – Jun 2023

Other Experience / Projects

Institute of Data Science (blog post) Mar 2025 – Aug 2025

• Provided statistical consulting to master’s and doctoral students in other departments on dissertation/thesis methodology.
• From fields such as education, psychology, and biology.
• Topics: repeated-measures ANOVA, mediation analysis, multilevel structural equation modeling (SEM).

Big Data Analysis for Industry-Academic Cooperation (blog post) Mar 2024 – Aug 2025

• Combined foundational lectures with project-based learning
• One semester for introduction, second semester for Kaggle-style project using open competition data
• Third semester for Company-sponsored projects using real corporate datasets to address ongoing business problems

Prediction of Housing Price (blog post) May 2024 – Jun 2024

• Applied LMM with 'region' factor as random effect
• Compared between R² by Nakagawa (2012) and Bayesian R² suggested by Gelman et al. (2019)

Customer Churn-out Prediction (blog post) Oct 2023 – Dec 2023

• Predicted whether a customer may go into outflow so as to save profits.
• Sorted out the meaningful variables through Ridge & Lasso first.
• Applied logistic regression after estimating the posterior of each coefficient using RStan.

Relevant Skills

Programming Languages: R, Rcpp, RStan, Python, PyTorch
Software and Tools: LaTeX

Language Proficiency

TOEFL iBT: 102 (R 23, L 26, S 26, W 27) Aug 10, 2025