Myungsub Choi
Myungsub Choi

Head of AI

Tynapse

About Me

I am the Head of AI at Tynapse, where I lead research on AI trust and safety for autonomous AI agents. Previously, I was a Staff Engineer at Samsung AI Center, building multimodal RAG applications for internal knowledge management. I received Ph.D. at Computer Vision Lab, Seoul National University under the supervision of Prof. Kyoung Mu Lee. I like discovering new insights from ambiguous problems and translating complex technical ideas into practical solutions.

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Interests
  • AI Trust & Safety
  • AI Agents
  • LLM / RAG
Education

  • PhD Electrical Engineering and Computer Science

    Seoul National University

  • BEng Electrical Engineering and Computer Science

    Seoul National University

Experience

  1. Head of AI

    Tynapse
    Leading research on AI trust and safety, building real-time monitoring and governance solutions for autonomous AI agents.

  2. Staff Engineer

    Samsung Electronics, DS Division, AI Center (formerly SAIT, AI Research Center)

    Responsibilities include:

    • AI Agent (Jun 2024 – Sep 2025): Built a multimodal Retrieval‑Augmented Generation (RAG) application for internal knowledge management, improving efficiency in accessing distributed information across teams.
    • AI ISP (Jan 2024 ‑ May 2024): Designed and trained a natural language‑based Image Quality Assessment (IQA) model, enabling intuitive and context‑aware image evaluations.
    • AI ISP (May 2022 ‑ Dec 2023): Developed an efficient dual‑pixel autofocus model optimized for low‑light environments, improving focusing speed and accuracy.

  3. Visiting Researcher

    Google Research

    Responsibilities include:

    • Conducted research on vision‑language models for controllable image editing guided by natural language instructions.
    • Proposed a novel approach using conditional classifier‑free guidance to enhance editing fidelity and semantic alignment.

  4. Research Intern

    Snap Inc.

    Responsibilities include:

    • Developed deep learning models for efficient and high‑quality video frame interpolation.
    • Designed and implemented the SNU‑FILM benchmark dataset for analytic evaluation.

Education

  1. PhD Electrical Engineering and Computer Science

    Seoul National University
    Integrated Master & Ph.D in EECS.
    Thesis: Test‑Time Adaptation Methods for Video Frame Interpolation.
    Supervised by Prof. Kyoung Mu Lee

  2. BEng Electrical Engineering and Computer Science

    Seoul National University
    GPA: 3.48/4.30
Recent Publications
Suyoung Lee, Myungsub Choi (2026). Beyond the Verdict: Evidence-Aligned Evaluation of Visual Prompt-Injection Guardrails. ECCV 2026 2nd Workshop on Benchmarking Evidence-Aligned Multimodal Reasoning (BEAM 2) (Oral).
PDF Preprint Site
SangJin Park, Myungsub Choi, Jineok Kim, Minseung Kang (2026). Risk Is Not Review Value: Wrong-Answer Exposure Under Bounded Review Budgets. KDD 2026 Workshop on Secure and Trustworthy Large Language Models (SeT-LLM) (Oral).
PDF Preprint Site
SangJin Park, Myungsub Choi, Jineok Kim, Minseung Kang (2026). Cross-Agent Campaign Attribution: Linking Asynchronous Attacks Across LLM Agents. ICML 2026 Second Workshop on Agents in the Wild: Safety, Security, and Beyond (AIWILD).
PDF Preprint Site
Sangwon Lee, Myungsub Choi, Nagyeong Lee, Hyong-Euk Lee (2025). Stable Autofocus with Focal Consistency Loss. Proceedings of the IEEE/CVF winter conference on applications of computer vision.
PDF DOI
Myungsub Choi, Hana Lee, Hyong-Euk Lee (2023). Exploring positional characteristics of dual-pixel data for camera autofocus. Proceedings of the IEEE/CVF International Conference on Computer Vision.
PDF DOI
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