✏️ Education

1. 2020.03~2026.02 B.S in Department of Industrial Information Systems Engineering, Seoul National University of Science and Technology

2. 2026.03~2028.02 M.S in Department of Department of Industrial Management Engineering, Korea University

   Smart Product System Lab, Adviser: Jun-Geol Baek

🎂 Date of Birth: 2001.05.28

📞 Phone: +82) 010-8314-5028

✉️ E-Mail: [email protected]

🐱 Github

****github.com/koojahyeob

💾 Tech Blog

****https://velog.io/@jja_jja/posts

🌳 Linkdin

https://www.linkedin.com/in/koojahyeob/

📄 Curriculum Vitae

KooJaHyeob_CV.pdf

📃 1. Paper Experience (International Jounral & Conference + Domestic Conference)

자세한 내용은 연구 포트폴리오에서 확인하실 수 있습니다.

1. Sanghyuk Moon, JaHyeob Koo, Younghoon Lee*, "ADR-Rec: Adaptive Disentanglement for Cross-Domain Sequential Recommendation with Cross Attention Gating Mechanisms", Elsevier Neurocomputing, 2 Dec 2025 (링크)
2. [Under Review] Jahyeob Koo, Soyeong Lee, Jongkwan Choi, Gyeong Taek Lee*, "FORTUNE Tree: FOrward Random-split opTimal Utility-based Node Exploration Tree", Elsevier Applied Soft Computing, 31 Dec 2025
3. Jahyeob Koo, YongHo Song, JaeHyeon Shim, SoYeong Lee, YoungHoon Lee* “LOL: Learning with One Lightweight Sensor-Aware Predictive Model For Sleep Quality”, IEEE International Conference on ICT Convergence, 20 Aug 2025 - Oral (링크)

1. 구자협, 송용호, *박규태, “헬스케어 라이프로그 데이터를 활용한 수면 품질 및 상태 예측: Tree 기반 머신러닝과 딥러닝 모델 사용에 대한 비교/분석”, 대한산업공학회, KAIST(한국과학기술원, 대전), 대한민국, (7 Nov. 2025) - 포스터발표
2. 문상혁, 구자협, *이영훈, “통합시퀀스를 활용한 시점 별 선호도 차별화 추천시스템”, 한국전자거래학회, 한양대학교(서울), 대한민국, (11, Oct. 2024)

💻 2. Research Experience

**Data Driven User Analysis Research**

Undergraduate Researcher, Seoul National University of Science and Technology Industrial Engineering

Jan. 2024 ~ Feb. 2025

**Center for Artificial Intelligence Research**

Undergraduate Researcher, Korea Institute of Science and Technology (KIST)

Mar. 2025 ~ Dec. 2025

서울과학기술대학교 산업공학과/데이터사이언스학과 데이터기반 사용자분석랩

• Advisor: Younghoon Lee
• Cross-Domain Sequential Recommendation System with Deep Learning
• Time-series data Analysis, Prediction

KIST 인공지능 연구단

• Advisor: Haesol Park
• Time-Series data collection, preprocessing (interpolation/extrapolation), and modular implementation
• Multimodal time series prediction for Crowd Management Technology Development (time series data, CCTV image data)
• 확인서

🥇 3. Awards and Honors