I am a 3rd year Ph.D. candidate advised by Prof. Kuk-Jin Yoon at Visual Intelligence Lab (VILab), Korea Advanced Institute of Science and Technology (KAIST).

My current research focuses on human motion prediction / generation and multimodal LLMs. Ultimately, my goal is to develop AI models that enrich human-computer and human-robot interactions, improving everyday life.

During my undergraduate years, I discovered my passion for developing computational algorithms through my research in computational fluid mechanics. This enthralling experience had lead me to pursue graduate studies, starting from computer vision-based manufacturing during my master’s degree at MNIL, KAIST. For my PhD degree, I have moved to VILab, KAIST to focus my research on AI for computer vision.

My CV can be found here.

Awards

• 2024 Qualcomm Innovation Fellowship Korea Awardee

Publications (Computer Vision)

Multi-modal Knowledge Distillation-based Human Trajectory Forecasting
J. Jeong, S. Lee, D. Park, G. Lee, K. Yoon
CVPR 2025
[paper] [code]

Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning
J. Jeong*, D. Park*, K. Yoon
CVPR 2024 Highlight (2.8% of submitted)
[paper] [code] [project page]

T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory
D. Park, J. Jeong, S. Yoon, J. Jeong, K. Yoon
CVPR 2024
[paper] [code]

Improving Transferability for Cross-domain Trajectory Prediction via Neural Stochastic Differential Equation
D. Park, J. Jeong, K. Yoon
AAAI 2024
[paper] [code]

Publications (Manufacturing)

Near-infrared inspection and machine learning-based prediction for semiconductor membrane cavity structures
M. Jeong, J. Jeong, T. Kim, B. J. Lee, J. Lee
NEMS 2023
[proceeding]

Predicting AFM topography from optical microscopes using deep-learning
J. Jeong, T. Kim, B. J. Lee, J. Lee
Advanced Intelligent Systems, 2022 / IF 7.4
Selected as inside back cover
[paper]

Simulation of Germanium-on-Nothing cavity’s morphological transformation using deep learning
J. Jeong, T. Kim, B. J. Lee, J. Lee
Micro and Nano System Letters, 2022 / IF 3.6
[paper]

PCA-based sub-surface structure and defect analysis for Germanium-on-Nothing using nanoscale surface topography
J. Jeong, T. Kim, B. J. Lee, J. Lee
Scientific Reports, 2022 / IF 4.6
[paper]

Cellular and biomolecular detection based on suspended microchannel resonators
J. Ko, J. Jeong, S. Son, J. Lee
Biomedical Engineering Letters, 2021 / IF 4.6
[paper]

3D Printed Polymer Photodetectors
S. H. Park, R. Su, J. Jeong, S. Z. Guo K. Qiu, D. Joung, F. Meng, M. C. McAlpine
Advanced Materials, 2018 / IF 29.4
[paper]

Projects

• 2023.2 ~ 2023.12 / Synthetic-to-Real domain adaptation for military object detection / LIG Nex1
  
• 2023.5 ~ 2023.12 / Surround view depth estimation for autonomous vehicle systems / Hyundai NGV
  
• 2024.6 ~ 2025.6 / Vehicle trajectory prediction for autonomous vehicle systems / Hyundai Motor Group