About Me

My name is Jongoh Jeong, a Ph.D. degree candidate in Robotics at the Korea Advanced Institute of Science and Technology (KAIST), South Korea, where I am advised by Prof. Kuk-Jin Yoon.  My research spans from data-efficient visual representation learning to robust domain adaptation/generalization in order to design effective visual learning algorithms for efficient data use 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.Eng. in Electrical Engineering, 2014 - 2020

Publication (* Equal contribution)

Workshop

• FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks
  Hunmin Yang*, Jongoh Jeong*, Kuk-Jin Yoon
  ICCV 2023 Workshop on Adversarial Robustness In the Real World (AROW 2023)

• 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) 

Conference

• FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks
  Hunmin Yang*, Jongoh Jeong*, Kuk-Jin Yoon
  The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), Feb., 2024.

• Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint Prediction
  Hwan-Soo Choi*, Jongoh Jeong*, Young Hoo Cho, Kuk-Jin Yoon, Jong-Hwan Kim.
  Robot Intelligence Technology and Applications (RiTA) 2023, Dec. 2023.

• 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. [Project]

Journal

• Adaptive Bayesian Optimization for Fast Exploration Under Safety Constraints
  Guk Han, Jongoh Jeong and Jong-Hwan Kim.
  IEEE Access. Apr. 2023. 

• 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. (*Equal contribution) 
  IEEE Transactions on Intelligent Transportation Systems (IEEE T-ITS), Sept. 2022. [Project]

Academic Activities

Reviewer

• IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2022-Present

• IEEE Access, 2022-Present

• NeurIPS Workshop on Machine Learning for Health (ML4H), 2020-Present