KAIST EE · NTU S-Lab (MMLab)

Understanding how actions transform the physical world.

I build egocentric and embodied AI systems that reason about tool use, physical interaction, and action-driven state changes.

I am an undergraduate researcher in Electrical Engineering at KAIST and a research intern at NTU S-Lab (MMLab). My work spans tool-centric egocentric video, latent-action and world models, and 3D/4D scene understanding. I am particularly interested in connecting human video and robot experience to build models that understand not only what is visible, but how actions change the world.

Egocentric Vision Latent Action & World Models 3D/4D Vision Embodied AI
Junsu Kim
Physical interaction · Tool use
Video and world models
Updates

Recent news

Feb 2026
C3G was accepted to CVPR 2026.
Jan–May 2026
Conducted research at NTU S-Lab (MMLab) under Prof. Ziwei Liu during an exchange semester in Singapore.
Research

Three connected research threads

My projects are connected by one question: how can AI understand the physical consequences of actions in real-world environments?

01
Egocentric Tool-Use Reasoning

Understanding why tools are selected, how they interact with target objects, and how physical states evolve in first-person video.

02
Latent Action & World Models

Learning action-centric representations from video priors and modeling how possible actions transform future world states.

03
3D/4D Scene Understanding

Building geometry-aware scene representations for dynamic visual understanding, reconstruction, and embodied interaction.

Publications

Selected work

1
Shulin Tian*, Junsu Kim*, Shuai Liu, Hao Li, Yujiao Shen, Sihan Li, Zhe Yang, Yeongon Kim, Runmao Yao, Yuhao Dong, Fangzhou Hong, Antonino Furnari, Jingkang Yang, Hongyuan Zhu, Ziwei Liu.
EMNLP 2026 · Under review Dataset & Benchmark Egocentric Vision Tool-Use Reasoning

* Equal contribution.

Experience

Research roles

S-Lab (MMLab), NTU
Jan 2026 – Present

Research Intern · Advisor: Prof. Ziwei Liu

  • Co-led EgoTools, a 100+ hour multimodal egocentric dataset and 1K-question benchmark for tool-centric reasoning in real-world videos.
  • Designed annotation and QA workflows, coordinated data collection and quality control, and contributed to model evaluation, failure analysis, and manuscript writing.
  • Continuing follow-up research on egocentric tool use and embodied video reasoning.
Computer Vision Lab (CVLAB), KAIST AI
Jun 2025 – Present

Undergraduate Researcher · Advisor: Prof. Seungryong Kim

  • Working on video-prior-based latent action learning, with a focus on data strategy, human/robot video priors, and embodied world modeling.
  • Studied feed-forward 3D reconstruction and novel-view synthesis with Gaussian Splatting, VGGT, and NoPoSplat, and contributed analysis tools and experiments to C3G.
Video and Image Computing Lab (VICLAB), KAIST
Dec 2024 – Jun 2025

Research Intern · Advisor: Prof. Mun Churl Kim

  • Reviewed modern object detection architectures from RCNN/YOLO families to vision transformers.
  • Implemented baselines for few-shot and anomaly detection tasks.
Education

Academic background

Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, South Korea
  • B.S. in Electrical Engineering
  • Mar 2021 – Expected Aug 2027
  • GPA: 4.10/4.30 · Major GPA: 4.19/4.30
Nanyang Technological University (NTU)
Singapore
  • Exchange Student, School of Electrical and Electronic Engineering
  • Jan 2026 – May 2026
Honors

Selected awards

  • KAIST Presidential Fellowship (15th) 2025 – Present
  • National Science & Engineering Scholarship for Academic Excellence 2025 – Present
  • KAIST EE Dean’s List Award Spring 2024 Awarded to the top 3% of EE students
  • KAIST Freshman Dean’s List Award Fall 2021 Awarded to the top 3% of first-year students
  • Woon Hae Scholarship (12th) 2025
  • KAIST Shared Lives Award · Top-ranked Recipient 2026
Beyond Research

Leadership & technical toolkit

Leadership: President of EERun, Google Student Ambassador, member of the Young Engineers Honor Society.

Programming: Python, C/C++, PyTorch, Git, LaTeX.

Research toolkit: video preprocessing, dataset curation, annotation pipelines, model evaluation, and 3D/vision experimentation.