Jongoh Jeong

Jongoh Jeong
jeong2 [at] kaist.ac.kr / [CV] [Google Scholar] [Github] [LinkedIn]

I am a Ph.D. student in the Robotics Program at Korea Advanced Institute of Science and Technology (KAIST), South Korea, advised by Prof. Kuk-Jin Yoon at Visual Intelligence Lab. My research is aimed at robust and data-efficient visual representation learning, domain adaptation/generalization, and transfer learning for designing effective visual learning algorithms with minimal human supervision.

📌 Education

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea

🏫 Ph.D. in Robotics (Advisor: Prof. Kuk-Jin Yoon), 2022 - Present

🎓 M.S. in Electrical Engineering (Advisor: Prof. Jong-Hwan Kim), 2020 - 2022

The Cooper Union for the Advancement of Science and Art, New York, NY, USA

🎓 B.E. in Electrical Engineering, 2014 - 2020 (*2016-2018: military duty leave)

📖 Publications
(W: Peer-reviewed Workshop, C: Peer-reviewed Conference, J: Peer-reviewed Journal, P: Pre-print)
Research Interests:

Computer Vision (robust/data-efficient representation learning, domain adaptation/generalization for continual learning)
Robotic/Machine Vision (autonomous driving, sensor fusion)
Machine Learning (robust, safe, trustworthy, adversarial AI)

[P3] Semantic Structure-Aware Generative Attacks for Enhanced Adversarial Transferability

Jongoh Jeong, Hunmin Yang, Jaeseok Jeong, and Kuk-Jin Yoon
Pre-print, Jun. 2025.

[Preprint]

[W3] Boosting Adversarial Transferability with a Generative Model Perspective

Jongoh Jeong, Hunmin Yang, and Kuk-Jin Yoon
Computer Vision and Pattern Recognition (CVPR) 2025
Workshop on Generative Models for Computer Vision (GMCV 2025), Jun. 2025.

[Paper][Web]

[C4] Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks

Hunmin Yang, Jongoh Jeong, and Kuk-Jin Yoon
European Conference on Computer Vision (ECCV), Sep. 2024.
(Oral, 8.37% of accepted, 2.33% of submitted)

[Paper][Project]

[P2] Task-oriented Learnable Diffusion Timesteps for Universal Few-shot Learning of Dense Tasks

Changgyoon Oh*, Jongoh Jeong*, Jegyeong Cho*, and Kuk-Jin Yoon
Preprint, Sep. 2024. (*Shared first authorship)

[Preprint]

[C3] FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks

Hunmin Yang*, Jongoh Jeong*, and Kuk-Jin Yoon (*Shared first authorship)
The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), Feb. 2024.
*Extension of [W2]

[Paper][Project]

[C2] Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint Prediction

Hwan-Soo Choi*, Jongoh Jeong*, Young Hoo Cho, Kuk-Jin Yoon, and Jong-Hwan Kim. (*Shared first authorship)
Robot Intelligence Technology and Applications (RiTA), Dec. 2023.

[Paper][Project]

[P1] Exploring Syn-to-Real Domain Adaptation for Military Target Detection

Jongoh Jeong, Youngjin oh, Gyeongrae Nam, Jeongeun Lee, and Kuk-Jin Yoon
Preprint, Oct. 2023.

[Preprint]

[W2] FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks

Hunmin Yang*, Jongoh Jeong*, and Kuk-Jin Yoon (*Shared first authorship)
ICCV 2023 Workshop on Adversarial Robustness In the Real World (AROW 2023), Oct. 2023.
[Paper][Project]

[J2] Adaptive Bayesian Optimization for Fast Exploration Under Safety Constraints

Guk Han, Jongoh Jeong, and Jong-Hwan Kim.
IEEE Access. Apr. 2023.

[Paper][Project]

[C1] Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse Weather

Jongoh Jeong and Jong-Hwan Kim.
British Machine Vision Conference (BMVC), Nov. 2022.

[Paper][Project]

[J1] End-to-end Real-time Obstacle Detection Network for Safe Self-driving via Multi-task Learning

Taek-Jin Song*, Jongoh Jeong* and Jong-Hwan Kim. (*Shared first authorship)
IEEE Transactions on Intelligent Transportation Systems (IEEE T-ITS), Sept. 2022.

[Paper][Project]

[W1] Using Privileged Information to Improve Prediction in Health Data: A Case Study.

Jongoh Jeong, Do Hyung Kwon, Min Joon So, Anita Raja, Shivani Ghatge, Nicolae Lari, and Ansaf Salleb Aouissi.
NeurIPS 2019 Workshop on Information Theory and Machine Learning (ITML 2019)

[Paper][Web]

🗂️ Research Projects

C-arm X-ray imaging system development for DK Medical Systems (Jun.'25~May'26)
AI/SW Project for Commissioned Education (Ministry of National Defense (MND), Jun.'22 – Dec.'26)
Synthetic Military Target Data Generation for Domain Adaptive Object Detection (LIGNex1, Oct.’22 – Sep.’23)
Development of Artificial Intelligence Technology that Continuously Improves Itself as the Situation Changes in the Real World
(Korea MSIT (IITP), No.2020-0-00440, Sep.’20 –Aug.’22)
Development of Real-time Smart Solution for Solder Mount Technology (SMT) (Koh-Young Tech., Sep.’20 – Aug.’22)

📤 Academic Activities

Reviewer

AAAI, 2026-Present
IEEE Transactions on Geoscience and Remote Sensing (T-GRS), 2024-Present
- IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2022-Present
IEEE Access, 2022-Present
NeurIPS Workshop on Machine Learning for Health (ML4H), 2020-Present

Professional Society Membership

- Order of the Engineer 2020 – Present
- IEEE-Eta Kappa Nu, Student Member 2018 – Present
- ACM, Student Member 2018 – Present

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