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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.

This table browses all dspace content
Issue Date	Title	Author(s)	Type	View	Altmetrics
2023-06	Chemistry-informed machine learning: Using chemical property features to improve gas classification performance	Kim, Yeram; Lim, Chiehyeon; Lee, Junghye, et al	ARTICLE	569	Chemistry-informed machine learning: Using chemical property features to improve gas classification performance
2023-04	Sensor drift compensation for gas mixture classification in batch experiments	Oh, YongKyung; Lee, Juhui; Kim, Sungil	ARTICLE	378	Sensor drift compensation for gas mixture classification in batch experiments
2023-03	Quantifying incident impacts and identifying influential features in urban traffic networks	Lee, JuYeong; Kwak, JiIn; Oh, YongKyung, et al	ARTICLE	1114	Quantifying incident impacts and identifying influential features in urban traffic networks
2023-02	Time delay estimation of traffic congestion propagation due to accidents based on statistical causality	Oh, YongKyung; Kwak, JiIn; Kim, Sungil	ARTICLE	704	Time delay estimation of traffic congestion propagation due to accidents based on statistical causality
2022-06	Multichannel convolution neural network for gas mixture classification	Oh, YongKyung; Lim, Chiehyeon; Lee, Junghye, et al	ARTICLE	999	Multichannel convolution neural network for gas mixture classification
2021-10	Maximum feasibility estimation	Kim, Sungil	ARTICLE	410	Maximum feasibility estimation
2021-04	혼합 가스 분류를 위한 전이학습 기반 방법론	오용경; 김남우; 김성일	ARTICLE	552	혼합 가스 분류를 위한 전이학습 기반 방법론
2021-04	시뮬레이션 데이터 생성을 통한 기계학습 기반 원자로 노심 이상 탐지 방법론	오용경; 김한주; 이덕중, et al	ARTICLE	629	시뮬레이션 데이터 생성을 통한 기계학습 기반 원자로 노심 이상 탐지 방법론
2020-10	Multiresolution spatial generalized linear mixed model for integrating multi-fidelity spatial count data without common identifiers between data sources	Kim, Sungil; Duan, Rong; Ma, Guang-Qin, et al	ARTICLE	549	Multiresolution spatial generalized linear mixed model for integrating multi-fidelity spatial count data without common identifiers between data sources
2020-08	선박 이상 탐지를 위한 VAE-CUSUM 기반 모니터링 방법론	박재민; 김성일	ARTICLE	685	선박 이상 탐지를 위한 VAE-CUSUM 기반 모니터링 방법론
2019-06	Revealing household characteristics using connected home products	Kim, Sungil	ARTICLE	758	Revealing household characteristics using connected home products
2019-06	A practical approach to measuring the impacts of stockouts on demand	Kim, Sungil; Kim, Heeyoung; Lu, Jye-Chyi	ARTICLE	847	A practical approach to measuring the impacts of stockouts on demand
2019-01	Spatial cluster detection in mobility networks: a copula approach	Kim, Heeyoung; Duan, Rong; Kim, Sungil, et al	ARTICLE	1020	Spatial cluster detection in mobility networks: a copula approach
2017-10	Incorporation of engineering knowledge into the modeling process: a local approach	Kim, Heeyoung; Vastola, Justin T.; Kim, Sungil, et al	ARTICLE	1332	Incorporation of engineering knowledge into the modeling process: a local approach
2017-03	An integrated holistic model of a complex process	Kim, Heeyoung; Kim, Sungil; Deng, Jianxin, et al	ARTICLE	1614	An integrated holistic model of a complex process
2017-02	Early detection of vessel delays using combined historical and real-time information	Kim, Sungil; Kim, Heeyoung; Park, Yongro	ARTICLE	1977	Early detection of vessel delays using combined historical and real-time information
2017-01	Batch Sequential Minimum Energy Design with Design-Region Adaptation	Kim, Heeyoung; Vastola, Justin T.; Kim, Sungil, et al	ARTICLE	1497	Batch Sequential Minimum Energy Design with Design-Region Adaptation
2016-09	Ordinal Classification of Imbalanced Data with Application in Emergency and Disaster Information Services	Kim, Sungil; Kim, Heeyoung; Namkoong, Younghwan	ARTICLE	1618	Ordinal Classification of Imbalanced Data with Application in Emergency and Disaster Information Services
2016-07	A new metric of absolute percentage error for intermittent demand forecasts	Kim, Sungil; Kim, Heeyoung	ARTICLE	1559	A new metric of absolute percentage error for intermittent demand forecasts
2015-09	Adaptive combined space-filling and D-optimal designs	Kim, Sungil; Kim, Heeyoung; Lu, Richard W., et al	ARTICLE	1283	Adaptive combined space-filling and D-optimal designs

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