Experience

  1. Graduate Researcher

    Yonsei University
    • Advised by Professor Ilmun Kim in Dept. of Statistics and Data Science
    • Developed a semi-supervised kernel two-sample test, analyzing its asymptotic properties and rigorously demonstrating its improved power by leveraging additional covariates
    • Presented the work at the 2024 Korean Statistical Society Winter Conference and the Brain Korea Student Seminar
    • Reviewed proofs and provided constructive feedback on the related works, which the authors acknowledged in their publications
    • Organized seminars with fellow graduate students to gain insights into advanced statistical topics
    • Working on kernel-based conditional independence testing

  2. Graduate Researcher

    Yonsei University
    • Advised by Professor Yongho Jeon at the Basic Research Laboratory in Dept. of Statistics and Data Science
    • Delivered a presentation, “Semi-Supervised Learning: Inference,” focusing on a general framework to ensure robustness and efficiency when incorporating unlabeled data into statistical models
    • Attended 48 weekly and biweekly presentations and explored the statistical foundations underlying modern machine learning and deep learning (e.g., transfer learning, watermarks for generative models, diffusion models)

  3. Teaching Assistant

    Yonsei University
    • (Fall 2023, Fall 2024, course: STA1001 “Introduction to Statistics”) Delivered weekly lectures in English, mentoring over 30 undergraduate students and helping them build a strong foundation in statistical methods
    • (Spring 2023, Fall 2023, Spring 2024, Fall 2024, course: STA3109 “Mathematical Statistics II”) Reviewed exam problems, graded, and provided detailed feedback for over 100 undergraduate students to support their academic growth, all conducted in English

  4. Part-time Researcher

    Yonsei University
    • Advised by Professor Sung-Rae Cho in Dept. of Rehabilitation Medicine
    • Performed statistical analyses on patient data using generalized linear models and explainable AI techniques to achieve accurate and interpretable results for medical professionals
    • Provided statistical guidance to predict the rehabilitative prognosis of spinal fusion surgery, focusing on identifying key factors and analyzing correlations between related variables while addressing challenges posed by missing data

  5. Teaching Assistant

    Seoul National University
    • (Summer 2023, course: “Machine Learning/AI-Based Research Methodologies in Child and Family Studies”) Reviewed and revised the course materials, introducing basic statistical learning methods for graduate students
    • Designed a section on classification algorithms and guided students in using R for data analysis.

  6. Undergraduate Research Intern

    Yonsei University
    • Advised by Professor Noseong Park at Big Data Analytics Lab. in Dept. of Computer Science
    • Proposed a hypernetwork model, HyperGPA, conducting extensive experiments with multiple forecasting benchmarks to demonstrate the model’s adaptability and effectiveness
    • Developed the research into papers
    • Investigated advanced deep learning methods for time series forecasting, focusing on Neural Ordinary Differential Equations to gain insights into the challenges presented by dynamic data environments

  7. Vice President, Head of Study Preparation Team

    Expanded Statistics Club, Yonsei University
    • Led weekly study sessions on topics such as Bayesian statistics, convex optimization, and deep learning, engaging over 30 participants
    • Prepared and taught a course on Statistical Learning Theory and Real Analysis, providing structured lessons to help peers build a strong theoretical foundation
    • Organized guest lectures to connect students with professionals in the field, fostering a collaborative and enriching learning environment

  8. Member

    Piano in Yonsei, Yonsei University
    • Performed J. Hurwitz’s La La Land Medley and M. Moszkowski’s Spanish Dance at outdoor concerts
    • Performed F. Chopin’s Etude Op. 25, No. 5 and E. Satie’s Gymnopédie in recitals, showcasing technical skill and musical expression.

Education

  1. MA in Statistics and Data Science

    Yonsei University

    GPA: 4.3/4.3 Advised by Prof Ilmun Kim. Presented ongoing work at the 2024 Winter Korean Statistical Society Conference and the 2024 Brain Korea Student Seminar. Courses included (* English-only class):

    • Statistical Theory for High Dimensional and Big Data*
    • Theoretical Statistics*
    • Statistical Learning Theory
    • Nonparametric Function Estimation
    • Functional Data Analysis*
    • Oscillatory Integral and its Applications
    • Harmonic Analysis 1
    • Real Analysis Ⅰ
    • Advanced Deep Learning
    • Recent Advances in Theoretical Machine Learning
    • Generalized Mixed Models for Data Science
    • Mathematical Statistics Ⅰ*
    • Linear Model

  2. Exchange Student

    University of Wisconsin Madison

    GPA: 4.0/4.0

    Courses included:

    • Introduction to Measure and Integration*
    • Statistical Methods for Epidemiology*
    • Mathematical Methods in Data Science*

  3. BA in Applied Statistics & BSc in Mathematics

    Yonsei University

    GPA: 4.14/4.3

    Courses included:

    • Probability and Random Processes
    • Stochastic Processes for Data Science
    • Categorical Data Analysis
    • Partial Differential Equations
    • Complex Analysis*
    • Theoretical Statistics(1)
    • Time Series Analysis
    • Survival Data Analysis*
    • General Topology* & Topology (2)*
    • Differential Geometry (1)
    • Modern Algebra (1)* & (2)*
    • Analysis (1) & (2)
Awards
Honorable Mention for Graduate Presentation, 2024 Winter Korean Statistical Society Conference
Korean Statistical Society ∙ December 2024
I was awarded for the originality of my research approach for two-sample test using kernel methods in semi-supervised settings and my ability to communicate complex ideas through my presentation.
Excellent Prize, 2023 Yonsei Big Data Analysis Competition
Yonsei University & Neovalue Co. ∙ September 2023
I was awarded for integrating real estate and public data to propose a merchandise display allocation using survival data and network analysis, recognized for its excellence in both the written report and oral presentation.
Semester High Honors
Yonsei University ∙ March 2023
I was recognized for my outstanding academic achievement by receiving Semester High Honors, awarded to students who maintain a GPA of 3.75/4.3 (or 3.5/4.0) or higher, placing within the top 3% of their class for the Fall semester in 2022.
Semester Honors
Yonsei University ∙ March 2022
I was recognized for my outstanding academic achievement by receiving Semester High Honors, awarded to students who maintain a GPA of 3.75/4.3 (or 3.5/4.0) or higher, placing within the top 10% of their class for the Fall semester in 2021.
Semester High Honors
Yonsei University ∙ March 2018
I was recognized for my outstanding academic achievement by receiving Semester High Honors, awarded to students who maintain a GPA of 3.75/4.3 (or 3.5/4.0) or higher, placing within the top 3% of their class for the Fall semester in 2017.
Semester Honors
Yonsei University ∙ September 2017
I was recognized for my outstanding academic achievement by receiving Semester High Honors, awarded to students who maintain a GPA of 3.75/4.3 (or 3.5/4.0) or higher, placing within the top 10% of their class for the Spring semester in 2017.
Skills & Hobbies
Technical Skills
Python
R
MATLAB
Hobbies
Walk
Soccer
Photography
Languages
100%
Korean
95%
English
40%
German