Contacts

• Email: [email protected]
• **Github / Linkedin / Google Scholar**

Education

• Ph.D. in AI, KAIST, 2023-Present
  • Thesis: Modeling and Controlling AI Behavior and a Case for Machine Psychopathology
  • Advisor: Kijung Shin, Ph.D.
  • GPA: 3.62/4.30
• M.S. in AI, KAIST, 2021-2023
  • Thesis: Towards Deep Attention in Graph Neural Networks: Problems and Remedies
  • Advisor: Kijung Shin, Ph.D.
  • GPA: 3.61/4.30
• B.S. in Psychology, UCSD, 2013-2016
  • Thesis: Mantram Repetition Program Reduces Depression Severity among Veterans with Major Depressive Disorder
  • Advisor: Sidney Zisook, M.D.
  • GPA: 3.84/4.00 (magna cum laude)

Awards

• Winner of Global AI Research Leap Challenge 2026, hosted by National AI Research Lab of Korea
• Outstanding Reviewer of KDD 2025 (top 10%)
• Best Reviewer of KDD 2024 (top 1.2%; 30/2558)

Featured Work.

Emergence of psychopathological computations in large language models [link]

TL;DR. We present the first mechanistic evidence of emergent computational processes of psychopathology (mental disorders) in LLMs.

• [Objective]. We require rigorous theoretical and empirical analyses.
• [Theory]. Our computational interpretation of the network theory of psychopathology allows its application to AI systems.