Data Analytics Lab

데이터 애널리틱스 연구실

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데이터 애널리틱스 연구실

다양한 산업 현장에서 발생하는 복잡한 공학 문제를 해결하는 새로운 통계 및 데이터 사이언스 방법론을 연구합니다. 특히, 제조와 물류 분야에서 발생하는 품질 향상, 이상 감지, 시스템 분석 연구를 진행하고 있습니다. 4차 산업혁명 시대에 산업 현장에 인공지능 기술을 접목하여 혁신적인 변화를 이끌어내는 연구에 관심을 가지고 있습니다.
Welcome to the Data Analytics Lab at the Ulsan National Institute of Science and Technology (UNIST). Our research focuses on development of novel statistical methods for solving complex engineering problems. Our team pursues leading-edge research in the field of data science and business analytics with industry, government, and community partners. Our research can be characterized by three aspects: i) statistics as a research methodology, ii) motivation from real data, and iii) applications to industry.

Major research field

System Monitoring & Anomaly Detection, Sequential Learning, Large-scale Calibration, and Uncertainty Quantification

Desired field of research

Artificial Intelligence in Quality Engineering

Research Keywords and Topics

Industrial Statistics and Data Analytics; Quality Engineering and Management; Response surface
methodology; Demand forecasting; Machine learning and Data mining; Business Analytics

Research Publications

• JuYeong Lee, JiIn Kwak, YongKyung Oh and Sungil Kim (2023), Quantifying Incident Impacts and Identifying Influential Factors on Urban Traffic Networks, Transportmetrica B: Transport Dynamics, 11(1), pp 279-300.
• Sungil Kim* (2021), Maximum feasibility estimation, Information Sciences, 575, pp 739-801.
• Sungil Kim, Rong Duan, Guang-Qin Ma, and Heeyoung Kim* (2020), Multiresolution spatial generalized linear mixed model for integrating multi-delity spatial count data without common identiers between data sources, Spatial Statistics, 39, 100467.
• Sungil Kim (2019), Revealing household characteristics using connected home products, Information Sciences, 486, pp 52-61.
• Sungil Kim, Heeyoung Kim, and Yongro Park (2017), Early detection of vessel delays using combined historical and real-time information, Journal of the Operational Research Society, 68(2), pp 182-191.


• Kim, Sungil (primary inventor), Method of anomaly detection of vessels applying Bayesian bootstrap. (10-2534357, granted May 16, 2023)
• Kim, Sungil (primary inventor), Sensor drift compensation method and device. (10-2364019, granted February 14, 2022)
• Kim, Sungil (primary inventor), Method and apparatus for determining delay possibility of shipment. (10-2250354, granted May 4, 2021)


  • SC. 경제/경영
  • SC09. 생산관리
  • SC0904. 품질관리


  • 정보-지식-지능화 사회 구현
  • 012300. 인공지능/지능로봇 기술


  • 녹색기술관련 과제 아님


  • IT 분야
  • 정보처리 시스템 및 S/W
  • 010316. 기타 정보처리시스템 및 S/W 기술