Research Experience
Naver CLOVA, Video team
- Research Internship, Jan., 2023 to Present
- Project (ongoing): Domain Generalization for Video Anomaly Detection
Hyundai Motor Company, Robotics Lab.
- Research Scholarship, June, 2019 to Present
- Project: Unsupervised Video Anomaly Detection in Surveillance System
Global Ph.D. Fellowship Program
- Project Manager, Mar. 2019 to Present
- Project (ongoing): Anomaly Detection System with Relation Embedding and Contextual Understanding in
Surveillance Videos
- Funding KRW 150 million for 5 years
Yonsei University
- Project Manager/ Researcher, Mar. 2018 to Present
- 2D-3D Feature Correspondence Learning for Virtual Scene Reconstruction
- Development of Smart Signal Management System Customized for National Roads
- Deep Identification and Tracking of Missing Person in Heterogeneous CCTV
- Emotional Intelligence Technology to Infer Human Emotion and Carry on Dialogue
- Development of the High‑precision Natural 3D View Generation Technology using
- Smart‑car Multi Sensor and Deep Learning
- Road Conditions and Autonomous Bus AI Data
Electronics and Telecommunications Research Institute
- Research Internship, June, 2017 to Aug., 2017
- Intelligent Convergence Research Laboratory
Linköping University, Sweden
- Exchange Student, Aug., 2016 to Feb., 2017
- Electrical Engineering, Faculty of Science and Engineering
Kyunghee University
- Undergraduate Intern, Mar., 2017 to Feb., 2018
- Development of Improving Method for Virtual View Synthesis Technology
Professional Activity
Reviewer for International Journals
- IEEE Transactions on Industrial Informatics (TII, IF: 11.648)
- Springer Artificial Intelligence Review (IF: 9.588)
- IEEE Transactions on Information Forensics and Security (TIFS, IF: 7.231)
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT, IF: 5.859)
- Elsevier Neurocomputing (IF: 5.779)
Awards
- 1st Visual Inductive Priors for Data‑Efficient Deep Learning Challenge, 4th place, ECCV Workshop
- Learning Temporally Invariant and Localizable Features via Data Augmentation for Video Recognition