학력
학사. 2014. 8 동국대학교 전자전기공학학과
석사. 2016. 2. 동국대학교 전자전기공학과
박사. 2023. 12. 애리조나주립대학교 컴퓨터공학과
주요 경력
- 2016.01~2020.01 주식회사 케이티 융합기술연구원
- 2023.10~2024.08 애리조나주립대학교 박사후연구원
- 2024.09~ 현재 서울과학기술대학교 컴퓨터공학과
연구 분야
영상신호처리, 생체정보인식, 인공지능, 기계학습
담당 교과목
- 선형대수학, 컴퓨터그래픽스
주요논문 및 저서
E. S. Jeon, M. P. Buman and P. Turaga, "Uncertainty-Aware Topological Persistence Guided Knowledge Distillation on Wearable Sensor Data," IEEE Internet of Things Journal, 2024.
E. S. Jeon, H. Choi, A. Shukla, Y. Wang, Y., H. Lee, M. P. Buman and P. Turaga, "Topological persistence guided knowledge distillation for wearable sensor data," Engineering Applications of Artificial Intelligence, 130, 107719, 2024.
E. S. Jeon, S. Lohit, R. Anirudh, and P. Turaga, "Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks," In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5, 2023.
H. Choi, E. S. Jeon, A. Shukla, and P. Turaga, "Understanding the role of mixup in knowledge distillation: An empirical study," In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 2319-2328, 2023.
저널 논문
E. S. Jeon, M. P. Buman and P. Turaga, "Uncertainty-Aware Topological Persistence Guided Knowledge Distillation on Wearable Sensor Data," IEEE Internet of Things Journal, 2024.
E. S. Jeon, H. Choi, A. Shukla, Y. Wang, Y., H. Lee, M. P. Buman and P. Turaga, "Topological persistence guided knowledge distillation for wearable sensor data," Engineering Applications of Artificial Intelligence, 130, 107719, 2024.
E. S. Jeon, H. Choi, A. Shukla, Y. Wang, M. P. Buman and P. Turaga, "Constrained Adaptive Distillation Based on Topological Persistence for Wearable Sensor Data," IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-14, 2023.
E. S. Jeon, H. Choi, A. Shukla, and P. Turaga, "Leveraging angular distributions for improved knowledge distillation," Neurocomputing, 518, 466-481, 2023.
E. S. Jeon, A. Som, A. Shukla, K. Hasanaj, M. P. Buman and P. Turaga, "Role of data augmentation strategies in knowledge distillation for wearable sensor data," IEEE internet of things journal, 9(14), 12848-12860, 2021.
◾ Robustness of topological persistence in knowledge distillation for wearable sensor data, EPJ Data Science, 2024전은솜
학술대회
E. S. Jeon, R. Khurana, A. Pathak, and P. Turaga, "Leveraging Topological Guidance for Improved Knowledge Distillation," In Proceedings of the ICML Workshop on Geometry-grounded Representation Learning and Generative Modeling (ICMLW), 2024.
E. S. Jeon, S. Lohit, R. Anirudh, and P. Turaga, "Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks," In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5, 2023.
H. Choi, E. S. Jeon, A. Shukla, and P. Turaga, "Understanding the role of mixup in knowledge distillation: An empirical study," In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 2319-2328, 2023.
E. S. Jeon, H. Choi, A. Shukla, Y. Wang, M. P. Buman, and P. Turaga, "Topological knowledge distillation for wearable sensor data," In Proceedings of the Asilomar Conference on Signals, Systems, and Computers, pp. 837-842, 2022.
◾ Jinyung Hong, Eun Som Jeon, Changhoon Kim, Keun Hee Park, Utkarsh Nath, Yezhou Yang, Pavan K. Turaga, Theodore P. Pavlic, Debiasing Global Workspace: A Cognitive Neural Framework for Learning Debiased and Interpretable Representations, NeurIPS 2024 Workshop on Behavioral Machine Learning, Vancouver Convention Center, 2024전은솜
◾ Jinyung Hong, Eun Som Jeon, Changhoon Kim, Keun Hee Park, Utkarsh Nath, Yezhou Yang, Pavan K. Turaga, Theodore P. Pavlic, A Cognitive Framework for Learning Debiased and Interpretable Representations via Debiasing Global Workspace, UniReps Workshop, Vancouver Convention Center, 2024전은솜
| 컴퓨터공학과
교수진소개
