사진

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Kim, Sungil (김성일)

Department
Department of Industrial Engineering(산업공학과)
Website
http://analytics.unist.ac.kr
Lab
Data Analytics Lab. (데이터 애널리틱스 연구실)
Research Keywords
산업인공지능, 품질공학, 산업통계, 데이터사이언스, Industrial AI, Quality Engineering, Industrial Statistics, Data Science
Research Interests
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.
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Issue DateTitleAuthor(s)TypeViewAltmetrics
2020-10Multiresolution spatial generalized linear mixed model for integrating multi-fidelity spatial count data without common identifiers between data sourcesKim, Sungil; Duan, Rong; Ma, Guang-Qin, et alARTICLE22 Multiresolution spatial generalized linear mixed model for integrating multi-fidelity spatial count data without common identifiers between data sources
2020-08선박 이상 탐지를 위한 VAE-CUSUM 기반 모니터링 방법론박재민; 김성일ARTICLE25 선박 이상 탐지를 위한 VAE-CUSUM 기반 모니터링 방법론
2019-06Revealing household characteristics using connected home productsKim, SungilARTICLE300 Revealing household characteristics using connected home products
2019-06A practical approach to measuring the impacts of stockouts on demandKim, Sungil; Kim, Heeyoung; Lu, Jye-ChyiARTICLE282 A practical approach to measuring the impacts of stockouts on demand
2019-01Spatial cluster detection in mobility networks: a copula approachKim, Heeyoung; Duan, Rong; Kim, Sungil, et alARTICLE520 Spatial cluster detection in mobility networks: a copula approach
2017-10Incorporation of engineering knowledge into the modeling process: a local approachKim, Heeyoung; Vastola, Justin T.; Kim, Sungil, et alARTICLE699 Incorporation of engineering knowledge into the modeling process: a local approach
2017-03An integrated holistic model of a complex processKim, Heeyoung; Kim, Sungil; Deng, Jianxin, et alARTICLE1029 An integrated holistic model of a complex process
2017-02Early detection of vessel delays using combined historical and real-time informationKim, Sungil; Kim, Heeyoung; Park, YongroARTICLE1238 Early detection of vessel delays using combined historical and real-time information
2017-01Batch Sequential Minimum Energy Design with Design-Region AdaptationKim, Heeyoung; Vastola, Justin T.; Kim, Sungil, et alARTICLE858 Batch Sequential Minimum Energy Design with Design-Region Adaptation
2016-09Ordinal Classification of Imbalanced Data with Application in Emergency and Disaster Information ServicesKim, Sungil; Kim, Heeyoung; Namkoong, YounghwanARTICLE985 Ordinal Classification of Imbalanced Data with Application in Emergency and Disaster Information Services
2016-07A new metric of absolute percentage error for intermittent demand forecastsKim, Sungil; Kim, HeeyoungARTICLE975 A new metric of absolute percentage error for intermittent demand forecasts
2015-09Adaptive combined space-filling and D-optimal designsKim, Sungil; Kim, Heeyoung; Lu, Richard W., et alARTICLE749 Adaptive combined space-filling and D-optimal designs
2015-03Layers of Experiments with Adaptive Combined DesignKim, Sungil; Kim, Heeyoung; Lu, Jye-Chyi, et alARTICLE777 Layers of Experiments with Adaptive Combined Design
2012-03Optimization of a Carbon Dioxide-Assisted Nanoparticle Deposition Process Using Sequential Experimental Design with Adaptive Design SpaceCasciato, Michael J.; Kim, Sungil; Lu, J. C., et alARTICLE769 Optimization of a Carbon Dioxide-Assisted Nanoparticle Deposition Process Using Sequential Experimental Design with Adaptive Design Space
2005-12A time prediction model of cursor movement with path constraintsHong, SeungKweon; Kim, SungilARTICLE672

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