CV
A pdf version CV.
Education
- Ph.D. in Statistics, Texas A&M University, 2021 - Present.
- Advisor: Dr. Anirban Bhattacharya.
- GPA: 4.0 / 4.0
- Master in Mathematics, Texas A&M University, 2023 - Present.
- Advisor: Dr. Jonathan W. Siegel. Co-working with Dr. Stephan Wojtowytsch.
- B.A in Economics and B.S. in Statistics, Seoul National Univeristy, 2013 - 2020.
- Minor in Computer Science and Engineering.
- Graduation with Honors (Summa Cum Laude).
- Conducted Mandatory Military Service during the undergrad (2014 - 2016).
- GPA (Overall, Major / Total): 3.96, 4.09 / 4.3
Publications
(* denotes equal contribution, alphabetically ordered authorship)
Published & Accepted Articles
- Jakwang Kim*, Jiyoung Park*, Anirban Bhattacharya (2025). “Robust Estimation in metric spaces: Achieving Exponential Concentration with a Fr'echet Median”. AISTATS 2025. Paper, Slides, Codes.
- Jiyoung Park, Ian Pelakh, Stephan Wojtowytsch (2023). “Minimum norm interpolation by perceptra: Explicit regularization and implicit bias”. NeurIPS 2023. Paper, Slides.
Preprints
- Jiyoung Park, Günay Doğan (2024). “Probabilistic U-Net with Kendall Shape Spaces for Geometry-Aware Segmentations of Images”. Arxiv.
Work experience
- NSF Math Sciences Graduate Internship.
- National Institute of Standards and Technology (NIST), Gaithersburg (2023.05.22 - 2023.07.28).
- Supervisor: Dr. Günay Doğan.
- Topic: Geometric shape analysis.
- Research Resident, KC-ML2 (2019.05 - 2021.02).
- Supervisor: Dr. Chan Y. Park.
- Research in Graph Neural Network and Reinforcement Learning.
- Software Engineer Intern, Naver Webtoon (2018.07 - 2018.08).
- Implemented HBase API for log-data processing, and compared the performance with SQL based API codes.
Teaching
- Teaching Assistant
- Stat 689: Special topics in Statistics-Advanced Bayes (Graduate) (Spring 2025)
- Stat 633: Advanced Bayesian Modeling and Computation (Graduate) (Fall 2024)
- Stat 438: Bayesian Statistics (Undergrad) (Spring 2024)
- Stat 445/645: Applied Biostatistics and Data Analysis (Master course) (Fall 2022).
- Stat 642: Methods of Stat II (Master course) (Spring 2022).
- Stat 652: Stat In Research II (Master course) (Fall 2021).
Skills
- Programming Languages: Python, R, C, Java, C++, Assembly (x86-64).
- Libraries & Framework: Pytorch, Rcpp, Linux, Git, SQL, Latex, HBase.