Jehyun Park

JEHYUN PARK

Currently a Research Intern in PI-Lab at Seoul National University. I am working on Optimizing Neural Networks and developing Generalization algorithms.

I’ve conducted research in few-shot learning and model-compression, focusing on solving Out-Of-Distribution problems and improving performance in low-paramter situations.
I am currently a B.S in Computer Science at Sungkyunkwan University.

My research aims to develop foundation models for better generalization through optimization and interpretibility. I am particularly interested in Offline-RL, State-Space-modeling and Circuit base understanding of DNNs.

Always feel free to reach out to me with things you find exciting. Always open for new ideas :)

Contacts: jaheon555@g.skku.edu | GitHub | LinkedIn

Announcements

Jan, 2026 Received Excellence Award in Undergraduate Paper Competition at KSC 2025 as a Sole Author for the paper Adaptation in Out-Of-Distribution via Sparse Autoencoders in Vision Transformers.
Dec, 2025 Joined PI-Lab at Seoul National University as a Research Intern, focusing on optimizing Transformer architecture and solving Reasoning tasks in Vision-Language-Action Models.
Sep, 2025 1st Place in the 2025 Samsung AI Challenge. Competed individually and received 1st Prize Award for Optimizing Large Language Model. Awarded 7,500$
Feb, 2025 2nd Place in the 20th Korean Economic Securities Derivatives Competition. Received Korea Exchange Chairman's Award for ETF design. Awarded 4,500$
Jan, 2025 Received Engineering Innovation Award from SungKyunKwan University for LLM-based Recommendation System project with iKooB Healthcare.

Selected Papers

MUART: Mobile-Use Agent Red-Teaming Framework

MUART: Mobile-Use Agent Red-Teaming Framework

Jehyun Park

Under review

Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback

Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback

Guijin Son, Jehyun Park, Seyeon Park, Sunghee Ahn, Youngjae Yu

Under review

Adaptation in Out-Of-Distribution via Sparse Autoencoders in Vision Transformers

Adaptation in Out-Of-Distribution via Sparse Autoencoders in Vision Transformers

Je Hyun Park*

KSC 2025