Jungbin Jun (전정빈)

I am an undergraduate student in Statistics at Inha University and an undergraduate researcher in the Theoretical Statistics Lab under the supervision of Prof. Ilsang Ohn. My current research centers on conformal inference under distribution shift and adaptive statistical inference. More broadly, I am interested in statistically reliable and computationally efficient learning methods, while gradually broadening my interests to include bandit problems, PAC-Bayesian methods, and trustworthy AI.

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Education

Inha University
B.S. in Statistics
  • GPA: 4.42 / 4.50 (Major: 4.46 / 4.50)
  • Early Graduation (3 years)
  • Rank 1/41 in the department

Publications

Online Conformal Inference with Retrospective Adjustment for Faster Adaptation to Distribution Shift
Jungbin Jun, Ilsang Ohn
arXiv preprint, 2025

Enables faster adaptation to distribution shift through retrospective adjustment in online conformal inference.

Early-stopped Aggregation: Adaptive Inference with Computational Efficiency
Ilsang Ohn, Shitao Fan, Jungbin Jun, Lizhen Lin
In preparation, 2026

Computationally efficient adaptive inference via early-stopped aggregation.

Reading Notes

I enjoy reading and writing proofs; these notes reflect my efforts to better understand statistics and machine learning.
  • Notes on PAC-Bayes and Online Bayesian Inference [PDF]
  • Notes on Random Processes [PDF]
  • Notes on Asymptotic Statistics [PDF]
  • Notes on Lasso Regression [PDF]
Additional notes will be added over time.

Scholarships and Awards

Excellence Scholarship
Inha University
Hanjin Group Scholarship
Inha University

Website template adapted from Jon Barron.