Beach, S.R.H., Brody, G.H., Lei, M.K,Kim, S., Cui, J., Philibert, R.A. (2014). Is Sero-tonin Transporter Genotype Associated with Epigenetic Susceptibility or Vulnerability?Examination of the Impact of SES Risk on Among African American Youth.Develop-ment and Psychopathology, 26(2), 289-304, (impact factor in 2017: 4.357).
Steven R.H. Beach, Man-Kit Lei, Gene H. Brody,Sangjin Kim, Allen W. Barton, MeeshaV. Dogan and Robert A. Philibert (2016). Parenting, SES-risk, and later Young AdultHealth: Exploration of opposing indrect effects via DNA methylation.Child Develop-ment, 87(1), 111-121, (impact factor in 2017: 3.779).
Sangjin Kima nd Schliekelman Paul (2016). Prioritizing Hypothesis Tests for HighThroughput Data.Bioinformatics, 32(6): 850-8.doi:10.1093/bioinformatics/btv608,(impact factor in 2017: 5.481).
Sangjin Kim and Susan Halabi (2016). High Dimensional Variable Selection with ErrorControl.Biomed Research International, doi:10.1155/2016/8209453, (impact factor in2017: 2.583) .
Seung Hee Cho, Yohan Choi, Sean Hyungwoo Kim,Sang Jin Kim, and Jongwha Chang(2017). Urinary bisphenol A versus serum bisphenol A concentration and ovarian repro-ductive outcomes among IVF patients: Which is a better biomarker of BPA exposure?Mol Cell Toxicol, 13: 351-359. doi:10.1007/s13273-017-0039-0,(impact factor in 2017:1.430).
Namsoo P.Kim, Brandom Cepeda, Jihye Kim, Guikuan Yue,Sangjin Kim, and HyunjinKim (IEEE CPS, December 27, 2018). IoT Controlled Screw-Type 3D Food PrinterUsing Single Line Design Technique .
Sangjin Kim, Jihye Kim, Brandom Cepeda and Namsoo P. Kim (IEEE CPS, December27, 2018). Single Line Design Technique to Improve the Accuracy of Drug DeliverySystem: Piston Type Extrusion.
Showaib Sarker, Michael Pokojovy, and Sangjin Kim∗, (2019). On the Performance ofVariable Selection and Classification via Rank-Based Classifier.Mathematics (SCIE),7(5), 457; https://doi.org/10.3390/math7050457 .
Sangjin Kim∗and Jong-Min Kim (2019). Two-Stage classification with SIS using anew filter ranking method in high throughput data.Mathematics (SCIE),7(6), 493;https://doi.org/10.3390/math7060493.
Abhijeet R Patil, Jongwha Chang, Ming-Ying Leung, and Sangjin Kim∗(2019).Analyz-ing high dimensional correlated data using feature ranking and classifiers. Computa-tional and Mathematical Biophysics,7(1); https://doi.org/10.1515/cmb-2019-0008.
Abhijeet R Patil and Sangjin Kim∗(2020). Combination of Ensembles of RegularizedRegression Models with Resampling-Based Lasso Feature Selection in High Dimen-sional Data.Mathematics (SCIE), 8(1), 110; https://doi.org/10.3390/math8010110.
Abhijeet Patil, Bong-Jin Choi and Sangjin Kim(2020). Improving the classification per-formance with group lasso based ranking method.Journal of Theoretical & Computa-tional Chemistry (SCIE), DOI: 10.1142/S021963362040009X.
Abhijeet Patil and Sangjin Kim(2020). Adaptive lasso weights based on normalizedfiltering scores in molecular big data.Journal of Theoretical & Computational Chem-istry(SCIE), DOI: 10.1142/S0219633620400106.
Sangjin Kim, Michael Pokojovy, and Xiang Wan (2020). The Taut String Approachto Statistical Inverse Problems: Theory and Application.Computational Mathemat-ics(SCIE), vol 382, https://doi.org/10.1016/j.cam.2020.113098.
Jong-Min Kim,Sangjin Kim*, and Seong-Tae Kim (2020). On the Relationship of Cryp-tocurrency Price with US Stock and Gold Price Using Copula Models.Mathemat-ics(SCIE), 8(11), 1859; https://doi.org/10.3390/math8111859
Alberto Marin, Kristopher Van Huss, John Corbett,Sangjin Kim, Jonathon Mohl; Bo-young Hong, Jorge Cervantes(2020). Human macrophage polarization in the responseto Mycobacterium leprae genomic DNA.Current Research in Microbial Sciences(SCIE).
Sang Ha Sung,Sangjin Kim, Min Ho Ryu (2020).A Comparative Study on the Perfor-mance of Machine Learning Models for the Prediction of Fine Dust: Focusing on Do-mestic and Overseas Factors.INNOVATION STUDIES:KCI.
Sang-Ha Sung, Sangjin Kim* (2021) A Study on Facial Expression Change Detec-tion Using Machine Learning Methods with Feature Selection Technique. Mathematics(SCIE),9(17), 2062; https://doi.org/10.3390/math9172062.
B Noh, H Yoon, C Youm*,SKim*, M Lee, H Park, B Kim, H Choi, Y Noh (2021). Pre-diction of Decline in GlobalCognitive Function Using Machine Learning with FeatureRanking of Gait and Physical Fitness Outcomes in Older Adults.International jouranlof environmental research and public health(SCIE), 18(21),11347;https://doi.org/10.3390/ijerph182111347 (SCIE).
M Lee, Y Noh, C Youm*,SKim*, H Park, B Noh, B Kim, H Choi, H Yoon (2021). Es-timating Health Related Quality of Life Based on Demographic Characteristics, Ques-tionaires, Gait Ability, and Physical Fitness in Korean Elderly Adults.Internationaljouranl of environmental research and public health(SCIE), 18(22),11816;https://doi.org/10.3390/ijerph182211816 (SCIE).
Hyun-Ji Shin, Hyemin Yoon, Sangjin Kim, Do-Young Kang(2022).Classification of Alzheimer’s Disease using Dual Phase 18F- Florbetaben Image with Ranked Based Feature Selection and Machine Learning, Appl.Sci. 2022,12,7355 https://doi.org/10.3390/app12157355 (SCIE).
Jong-Min Kim, Hope.Han Kim, Sangjin Kim*(2022). Forecasting Crude Oil prices with Major SP 500 Stock Prices: Deep Learning, Gaussian Process, and Vine Copula, Axioms 2022,11,375. https://doi.org/10.3390/axioms11080375 (SCIE).
Sang-Ha Sung, Jong-Min Kim, Byung-Kown Kim, Sangjin Kim*(2022). A Study on Cryptocurrency Log Return Price Prediction Using Multivariate Time-Series Model, Axioms 2022,11(9), 448. https://doi.org/10.3390/axioms11090448 (SCIE)
Hyunji Shin, Soomin Jeon, Youngsoo Seol, Sangjin Kim, and Doyoung Kang(2023). Vision Transformer Approach for Classification of Alzheimer's Disease Using 18F-Florbetaben Brain Images, Appl.Sci. 2023. 13(6),3453. https://doi.org/10.3390/app13063453 (SCIE)
Sang Ha Sung, Chang Sung Seo, Min Ho Ryu, Sangjin Kim*(2023). Comparison of Machine Learning Methods Using Time series Data: Focusing on Inverter Data, Int. J. of Environment, Workplace and Employment, volume 7 issue 1, July 13, 2023, pp 13-33 https://doi.org/10.1504/IJEWE.2023.132428 (Scopus)
Yoonjae Noh, Jong-Min Kim, Sangjin Kim*(2023). Deep Learning Model for Multivariate High-frequency Time-Series Data: Financial Market Index Prediction, Mathematics, 2023,11(16), 3603; https://doi.org/10.3390/math11163603 (SCIE)
Yoonjae Noh, Yongil Yoon, Sangjin Kim*(2024.2). Two Stage Classification Method for Individual Workout Status Prediction with Machine Learning Apporoach, Measurement, Volume22, 2024, issue1, page 121-129; https://doi.org/10.1080/15366367.2023.2246109
Hyemin Yoon, HyunJin Kim, Sangjin Kim*(2024.2). Validation and Implementation of Customer Classification System using Machine Learning. Measurement: Interdisciplinary Research and Perspective, https://doi.org/10.1080/15366367.2023.2246111.
Jong-Min Kim, Il Do Ha & Sangjin Kim*(2024.8). Copula deep learning control chart for multivariate zero inflated count response variables, Journal of Theoretical and Applied Statistics, Volume58, 2024, Issue3, page 749-769, https://doi.org/10.1080/02331888.2024.2364688
Sang-Ha Sung, Soongoo Hong, Hyung-Rim Choi, Do-Myung Park, Sangjin Kim*(2024.8). Enhancing Fault Diagnosis in IoT Sensor Data through Advanced Preprocessing Techniques, Electronics 13(16):3289, DOI:10.3390/electronics13163289
Sang-Ha Sung, Soongoo Hong, Jong-Min Kim, Do-Young Kang, Hyuntae Park, Sangjin Kim* (2024.9). Cognitive Impairment Classification Prediction Model Using Voice SIgnal Analysis, Electronics, 13(18):3644, DOI:10.3390/electronics13183644
Hyemin Yoon, Do-Young Kang, Sangjin Kim*(2024.11). Enhancement and evaluation for deep learning-based classificaiton of volumetric neuroimaging with 3D-to-2D knowledge sistillation, Scientific Reports, 14(1), DOI:10.1038/s41598-024-80938-6
Youchang Song, Sangjin Kim*(2024). A Study on Deeping Learning-Based Emerging Commercial District Growth Prediction Model with with Big Data from Dongbaekjeon, JIIS, 2024,vol.30,no.3,pp.327-351(25 pages)(KCI)
송위창, 김상진*(2025). 지역화폐거래 데이터를 활용한 신흥 상군 연구: 부산시 동백전을 중심으로, 경영정보학연구, 2025,vol.27, no.1, pp.27-46(20 pages) (KCI)
노윤재, 김상진*(2025). 소형 객체 탐지 데이터를 활용한 원거리 도로 표지판 탐지 인공지능 모델링, 인터넷전자상거래연구, 2025, vol.25, no.1, pp.147-162(16 pages)(KCI)
성상하, 김상진*(2025). 항로표지 전압 데이터를 활용한 오토인코더기반 이상 탐지 분석, 인터넷전자상거래연구, vol.25, no.1, pp. 33-44(12 pages)(KCI)
Hyemin Yoon, Hoe-Kyoung Kim, Sangjin Kim*(2025.4). PPDD: Egocentric Crack Segmentation in the Port Pavement with Deep Learning-Based Methods, Appl. Sci. 2025, 15(10), 5446; https://doi.org/1-0.3390/app15105446
Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim* (2025.6). Enhancing the Accuracy of Image Classification for Degenerative Brain Diseases with CNN Ensemble Models Using Mel-Spectrograms, Mathematics 2025, 13(13), 2100; https://doi.org/10.3390/math13132100
Yoonjae Noh and SangjinKim* (2025.8). Zero-Shot Learning for S&P 500 Forecasting via Constituent-Level Dynamics: Latent Structure Modeling Without Index Supervision, Mathematics 2025,13(17), 2762; https://doi.org/10.3390/math13172762
Jong-Min Kim, Il Do Ha and Sangjin Kim*(2025.9). Deep learning-based survival analysis with copula-based activation functions for multivariate response prediction, Comput Stat (2025), https://doi.org/10.1007/s00180-025-01669-4
Hyemin Yoon, Sangjin Kim*(2025.9). Open-Vocabulary Crack Object Detection Through Attribute-Guided Similarity Probing, Appl. Sci. 2025, 15(19),10350; https://doi.org/10.3390/app151910350