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김성일
Kim, Sungil

김성일

Department of Industrial Engineering(산업공학과)

Research Interests
Industrial AI;Quality Engineering;Industrial Statistics;Data Science;산업인공지능;품질공학;산업통계;데이터사이언스
Lab Description
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.
Researcher ID Research Gate ORCiD Scopus Google Scholar
Previous
Domain-knowledge-informed functional outlier detection for line quality control systems File

Mun, Jong Hwan , Yoo, Jitae , Kim, Heesun , Ryu, Nayi , Kim, Sungil

Article Issue Date2024-03 View14
Spatially-correlated time series clustering using location-dependent Dirichlet process mixture model File

Jung, Junsub , Kim, Sungil , Kim, Heeyoung

Article Issue Date2024-02 View18
Grid-Based Bayesian Bootstrap Approach for Real-Time Detection of Abnormal Vessel Behaviors From AIS Data in Maritime Logistics File

Oh, YongKyung , Kim, Sungil

Article Issue Date2023-11 View5
Sensor drift compensation for gas mixture classification in batch experiments File

Oh, YongKyung , Lee, Juhui , Kim, Sungil

Article Issue Date2023-10 View8
Chemistry-informed machine learning: Using chemical property features to improve gas classification performance File File

Kim, Yeram , Lim, Chiehyeon , Lee, Junghye , Kim, Sungil , Kim, Sewon , Seo, Dong-Hwa

Article Issue Date2023-06 View7
Quantifying incident impacts and identifying influential features in urban traffic networks File

Lee, JuYeong , Kwak, JiIn , Oh, YongKyung , Kim, Sungil

Article Issue Date2023-03 View9
Time delay estimation of traffic congestion propagation due to accidents based on statistical causality File File

Oh, YongKyung , Kwak, JiIn , Kim, Sungil

Article Issue Date2023-02 View15
Multichannel convolution neural network for gas mixture classification File

Oh, YongKyung , Lim, Chiehyeon , Lee, Junghye , Kim, Sewon , Kim, Sungil

Article Issue Date2022-06 View15
Maximum feasibility estimation File

Kim, Sungil

Article Issue Date2021-10 View8
시뮬레이션 데이터 생성을 통한 기계학습 기반 원자로 노심 이상 탐지 방법론 File

오용경 , 김한주 , 이덕중 , 김성일

Article Issue Date2021-04 View7
혼합 가스 분류를 위한 전이학습 기반 방법론 File

오용경 , 김남우 , 김성일

Article Issue Date2021-04 View12
Multiresolution spatial generalized linear mixed model for integrating multi-fidelity spatial count data without common identifiers between data sources File

Kim, Sungil , Duan, Rong , Ma, Guang-Qin , Kim, Heeyoung

Article Issue Date2020-10 View6
선박 이상 탐지를 위한 VAE-CUSUM 기반 모니터링 방법론 File

박재민 , 김성일

Article Issue Date2020-08 View5
A practical approach to measuring the impacts of stockouts on demand File

Kim, Sungil , Kim, Heeyoung , Lu, Jye-Chyi

Article Issue Date2019-06 View7
Revealing household characteristics using connected home products File

Kim, Sungil

Article Issue Date2019-06 View5
Spatial cluster detection in mobility networks: a copula approach File

Kim, Heeyoung , Duan, Rong , Kim, Sungil , Lee, Jaehwan , Ma, Guang-Qin

Article Issue Date2019-01 View5
Incorporation of engineering knowledge into the modeling process: a local approach File

Kim, Heeyoung , Vastola, Justin T. , Kim, Sungil , Le, Jye-Chyi , Grover, Martha A.

Article Issue Date2017-10 View10
An integrated holistic model of a complex process File

Kim, Heeyoung , Kim, Sungil , Deng, Jianxin , Lu, Jye-Chyi , Wang, Kan , Zhang, Chuck , Grover, Martha A. , Wang, Ben

Article Issue Date2017-03 View9
Early detection of vessel delays using combined historical and real-time information File

Kim, Sungil , Kim, Heeyoung , Park, Yongro

Article Issue Date2017-02 View4
Batch Sequential Minimum Energy Design with Design-Region Adaptation File

Kim, Heeyoung , Vastola, Justin T. , Kim, Sungil , Lu, Jye-Chyi , Grover, Martha A.

Article Issue Date2017-01 View5
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