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 academic background is primarily in statistics, with additional coursework in mathematics. I am interested in reliability and uncertainty in modern AI, especially in problems related to trustworthy AI. My current work lies at the intersection of online learning, conformal inference, and adaptive statistical inference.

Email  /  CV  /  Github  /  Blog

Education
Inha University
B.S. in Statistics
Mar 2022 - Sep 2026 (Expected)
  • 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
paper / code

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
2023, 2025
Hanjin Group Scholarship
Inha University
2026

Website template adapted from Jon Barron.