Research

​GLOW-AI Education and Research Group for Cultivating Innovative Talent, 2025. 03~ 

• The GLOW-AI Education and Research Group is part of the BK21 FOUR program, a national initiative by the Ministry of Education of Korea to foster innovative talent in the field of artificial intelligence. 

Data-driven Intelligent Mobility Research Center, 2024.07~

• The Data-Driven Intelligent Mobility Research Center is part of the ITRC program funded by IITP under the Ministry of Science and ICT of Korea. It focuses on data-centric approaches to intelligent mobility, including driver state detection and in-vehicle network (CAN) security. 

Korea Data Science Consortium - Regional Innovation and Convergence Talent Development Program, 2023.09~ 

• The Korea Data Science Consortium Program is supported by the Ministry of Science and ICT to foster data science professionals tailored to regional industrial demands. It aims to drive regional innovation through practical, demand-oriented data science education and training programs. 

(New) Liyanage L. S. P., I. Park, and J. Kim, "ECG-Based Sleep Apnea Detection Using Hybrid DLinear Model," KDBC 2025, to be presented, Gyeongju, Korea, November 2025.

(New) J. Hong, I. Park, and J. Kim, "Graph-Spectral Filtering and QI Adaptive-ATAR Based EEG Preprocessing for ADHD Classification," KDBC 2025, to be presented, Gyeongju, Korea, November 2025.

(New) C. Lee, I. Park, and J. Kim, "Cross-Attention Learning of R-Peak Feature Interactions on Scalograms for Sleep Apnea Detection,"  KDBC 2025, to be presented, Gyeongju, Korea, November 2025.

S. Yun, Y. Suh, and J. Kim, "Sleep Stage Classification with Wearable Device Data using a Cross Attention Hybrid Fusion Model," KCC 2025, pp. 301-303 (oral), Jeju, Korea, July 2025.

H. Kwon and J. kim, "Effect of Data Augmentation in Arrhythmia Classification using Electrocardiogram Signal," KCC 2025, pp. 1434-1436 (oral), Jeju, Korea, July 2025.

Y. Kang, Liyanage L. S. P., and J. Kim, "Real-World Driver Stress Level Classification Using AffectiveROAD and Attention-Driven 1D CNN Architecture," KCC 2025, pp. 316-318 (poster), Jeju, Korea, July 2025.

T. Lee, J. Kim, "Rapid Spread and High Prevalence of the Pine Wilt Disease Around Wildfire Areas", Trees, Forests and People, pp. 100805, 2025 (Article In Press).

Y. Kang, Y. Suh, J. Kim, "A Multifaceted Time Series-Image Transformation and Integration Based Sleep Apnea Classification", IPIU 2025, pp. 256-258 (poster), Jeju, Korea, February 2025.

Y. Kang, J. KIm, "Major Depressive Disorder Classification Using Multichannel Images and Electroencephalography Signal ", KSC 2024, pp. 256-258 (oral), Yeosu, Korea, December 2024. (Best Paper Award - Database Section)

Y. Hong, J. Kim, "Parkinson's Disease Classification Using a Hybrid Deep Learning Ensemble with Bayesian Optimization", KSC 2024, pp. 292-294 (oral), Yeosu, Korea, December 2024.

S. Yoon, Y. Kang, J. Kim, "Classification of Abnormal Heart Sounds Using Scalogram-Based Image Transformation", KICS 2024, pp. 548-549 (oral), Gyeongju, Korea, November 2024.

Y. Hong, J. Kim, “XGB-PDNet : A Deep Learning Ensemble Model for Parkinson’s Disease Classification Using Keyboard Input Data”, KCC2024, pp. 375-377 (oral), Jeju, Korea, June 2024.

I. Park, Y.Suh, J. Kim, “Impact of Filter Order of Performance of Sleep Apnea Detection Deep Learning Models on ECG Signals”, KCC2024, pp. 1498-1500 (oral), Jeju, Korea, June 2024.

I. Park, J. Kim, "Semiconductor Wafer Bin Map Defect Pattern Classification based on Transfer Learning Considering Data Class Imbalance", to appear in Journal of the Korean Academia-Industrial cooperation Society, May 2024

Y. Park, J. Kim, "CRUNet: A Sleep Apnea Classification Model Utilizing Single-Lead Electrocardiogram Data with Optimal Feature Extraction Combination", Journal of KIISE Transactions on Computing Practices, vol. 30, no. 5, pp. 228-235, May 2024.

S. Heo, J. Kim, "A Study on Machine Learning-Based Estimation of Roadkill Incidents and Exploration of Influencing Factors",  Journal of Environmental Impact Assessment (JEIA), Vol. 33, no. 2, pp. 74-83, April 2024

I. Park, Y. Suh, J. Kim, "Sleep Apnea Classification using Time-Series Data Image Transformation Algorithm", KSC2023, pp. 627-629, Busan, Korea, Dec. 2023 (Best Paper Award - Artificial Intelligence Section)

Y. Park, Y. Suh, J. Kim, "Optimizing Sleep Apnea Classification based on Single-lead ECG Data", KDBC2023, pp. 61-64, Busan, Korea, Nov. 2023

D.W. Seo, J. Kim, H.W. Lee, Y. K. Suh, “A Deep Neural Network Based Wake-After-Sleep-Onset Time Aware Sleep Apnea Severity Estimation Scheme Using Single-Lead ECG Data”, IEEE Access, vol. 11, pp. 43720-43732, 2023

Y. Suh, S. Kim, J. Kim, “CLUTCH A Clustering-Driven Runtime Estimation Scheme for Scientific Simulations”  IEEE Access, vol. 8, pp. 220710-220722, 2020, doi: 10.1109

S. Kim, Y. Suh, J. Kim, “EXTES: An Execution-Time Estimation Scheme for Efficient Computational Science and Engineering Simulation via Machine Learning”, IEEE Access, vol. 7, pp. 98993-99002, 2019

J. K. Park, J. Kim, S. J. Kang, “A Situation-Aware Indoor Localization (SAIL) System Using a LF and RF Hybrid Approach”, MDPI Sensors 18, no. 11: 3864, 2018

 J. Kim, A. Helmy, “Analysing the mobility, predictability and evolution of WLAN users “, International Journal of Autonomous and Adaptive Communications Systems, Vol. 7, Nos. 1/2, pp. 169 - 191, Jan. 2014