(*corresponding author, † equal contribution)

2024

1. Dongcheol Lim†, Hyewon Kang†, Beomseok Choi, Woonki Hong*, and Junghye Lee*, "An Interpersonal Dynamics Analysis Framework with Accurate Voice Activity Detection Using Commercial Recording Sensors" (accepted at  IEEE Access).

2. Taek-Ho Lee†, Suhyeon Kim†, Junghye Lee*, and Chi-Hyuck Jun*, "HarmoSATE: Harmonized Embedding-based Self-attentive Encoder to Improve Accuracy of Privacy-preserving Federated Predictive Analysis", Information Sciences, 662, March 2024.

Working Papers

3. Yejin Kim†, Taek-Ho Lee†, Daeseong Jeon, HyeRim Park, Changyong Lee, and Junghye Lee*, "GC-RED: Graph Convolution-based Recurrent Encoder-Decoder for anomaly diagnoses in multivariate time-series data" (under revision at Applied soft computing).

4. Suhyeon Kim†, Taek-Ho Lee†, and Junghye Lee*, "TMF-GNN: Temporal Matrix Factorization-based Graph Neural Network for Multivariate Time Series Forecasting with Missing Values" (under revision at Expert Systems with Applications).

5. Hyewon Kang†, Taek-Ho Lee†, and Junghye Lee*, "RP-GCN: A recurrence plot based graph convolutional network for time series classification" (submitted to Applied soft computing).

6. Wonho Sohn†, Suhyeon Kim†, Dongcheol Lim, Hyerim Park, Wonji Lee, Junho Kim, Hwansung Yu, and Junghye Lee*, "MDL-FR: Multi-modal Deep Learning-based Fashion Recommendation with Styles" (submitted to Expert Systems with Applications).

7. Wonho Sohn†, Suhyeon Kim†, Dongcheol Lim, and Junghye Lee*, "ITSG-LSTM: Inter-country Trade Similarity Graph-based Long Short-Term Memory for Port Throughput Prediction" (submitted to Applied soft computing).

2023

8. Taek-Ho Lee†, Suhyeon Kim†, Junghye Lee*, and Chi-Hyuck Jun*, "Word2Vec-based Efficient Privacy-preserving Shared Representation Learning for Federated Recommendation System in a Cross-device Setting", Information Sciences, 651, December 2023.

9. Kyeongbin Kim†, Yoontae Hwang†, Dongcheol Lim, Suhyeon Kim, Junghye Lee*, and Yongjae Lee*, "Household Financial Health: A Machine Learning Approach for Data-driven Diagnosis and Prescription", Quantitative Finance, 23(11), 1565-1595, September 2023.

10. Jaeho Kim†, Hyewon Kang†, Jaewan Yang, Haneul Jung, Seulki Lee, and Junghye Lee*, "Multitask Deep Learning for Human Activity, Speed, and Body Weight Estimation using Commercial Smart Insoles", IEEE Internet of Things Journal, April 2023.

11. Yeram Kim, Chiehyeon Lim*, Junghye Lee, Sungil Kim, Sewon Kim, and Dong-Hwa Seo, "Chemistry-informed machine learning: Using chemical property features to improve machine learning with sensor data", Chemometrics and Intelligent Laboratory Systems, 237, June 2023.

12. Hojin Cho†, Kyeongbin Kim†, Kihyuk Yoon*, Jaewook Chun, Jaeyong Kim, Kyeongmin Lee, Junghye Lee*, and Chiehyeon Lim*, "MMP Net: A Feed Forward Neural Network Model with Sequential Inputs to Represent Continuous Multistage Manufacturing Processes without Intermediate Outputs", IISE Transactions, 1-12, September 2023.

2022

13. Seok-Ju Hahn†, Suhyeon Kim†, Young Sik Choi, Junghye Lee*, and Jihun Kang*, "Prediction of Type 2 diabetes Using Genome-wide Polygenic Risk Score and Metabolic Information: A Machine Learning Analysis of Population-based 10-year Prospective Cohort Study", eBioMedicine, 86, December 2022. (YTN Science [link], Donga Science [link])

14. Jae-Young Kim, Eo-Jin Hwang, Junghye Lee, Eunjung Kim*, and Dong-Wook Kim*, "Patient-specific molecular response dynamics can predict the possibility of relapse during the second treatment-free remission attempt in chronic myelogenous leukemia", Neoplasia, October 2022.

15. Seok-Ju Hahn, Minwoo Jeong, and Junghye Lee*, "Connecting Low-Loss Subspace Learning for Personalized Federated Learning", The 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), August 2022.

16. MyoungHoon Lee†, Suhyeon Kim†, Hangyeol Kim, and Junghye Lee*, "Technology Opportunity Discovery using Deep Learning-based Text Mining and a Knowledge Graph", Technological Forecasting and Social Change, 180, July 2022.

17. YongKyung Oh, Chiehyeon Lim, Junghye Lee, Sewon Kim, and Sungil Kim*, "Multichannel Convolution Neural Network for Gas Mixture Classification", Annals of Operations Research, 1-35, April 2022.

18. Suhyeon Kim, Hangyeol Kim, Eun-Sol Lee, Chiehyeon Lim, and Junghye Lee*, "Risk Score-embedded Deep Learning for Biological Age Estimation: Development and Validation", Information Sciences, 586, 628-643, March 2022.

2021

19. Dwi Yuli Rakhmawati and Junghye Lee*, "A product acceptance decision-making method based on process capability with considering gauge measurement errors", Communications in Statistics – Theory and Methods, July 2021.

20. Suhyeon Kim†, Wonho Sohn†, Dongcheol Lim, and Junghye Lee*, "A multi-stage data mining approach for liquid bulk cargo volume analysis based on bill of lading data", Expert Systems with Applications, 183, November 2021.

21. Junghye Lee*, Suhyeon Kim, Yejin Kim, and Hyewon Kang, "Artificial Intelligence Technology Trend Viewed through NeurIPS 2020" (published by National Information Society Agency, NIA), March 2021.

22. Taek-Ho Lee, Junghye Lee*, and Chi-Hyuck Jun*, "Bilingual Autoencoder-based Efficient Harmonization of Multi-source Private Data for Accurate Predictive Modeling", Information Sciences, 568, 403-426, August 2021.

23. Junghye Lee*, Inyoung Choi, and Chi-Hyuck Jun, "An efficient multivariate feature ranking method for gene selection in high-dimensional data", Expert Systems with Applications, 166, March 2021.

2020

24. Junghye Lee*, Junyong Jeong, and Chi-Hyuck Jun, "Markov blanket-based universal feature selection for classification and regression of mixed-type data", Expert Systems with Applications, 158, November 2020.

25. Suhyeon Kim, Haecheong Park, and Junghye Lee*, "Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis", Expert Systems with Applications, 152, August 2020.

26. Junghee Lee, Daehyun Han, Minso Shin, Jungho Im*, Junghye Lee, and Lindi Quackenbush, "Different spectral domain transformation for land cover classification using convolutional neural networks with multi-temporal satellite imagery", Remote Sensing, 12(7), March 2020.

2019

27. Miran Kim, Junghye Lee*, Lucila Ohno-Machado, and Xiaoqian Jiang, "Secure and differentially private distributed logistic regression for horizontally distributed data", IEEE Transactions on Information Forensics and Security, 15, 695-710, June 2019.

2018

28. Miae Kim, Junghee Lee, Daehyun Han, Minso Shin, Junghye Lee, Lindi Quackenbush, Zhu Gu, and Jungho Im*, "Convolutional neural network-based land cover classification using 2-D spectral reflectance curve graphs with multi-temporal satellite imagery", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(12), 4604-4617, December 2018. 

29. Junghye Lee, Ryeok-Hwan Kwon, Hyeong-Woo Kim, Sung-Hong Kang, Kwang-Jae Kim, and Chi-Hyuck Jun*, "A data-driven procedure of providing health promotion program for hypertension prevention", Service Science, 10(3), 289-301, September 2018.

30. Yingxiang Huang†*, Junghye Lee†, Shuang Wang, Jimeng Sun, Hongfang Liu, and Xiaoqian Jiang, "Privacy-preserving harmonization of distributed word embedding from different sources", Journal of Medical Internet Research Medical Informatics (†: equal contribution), 6(2), May 2018.

31. Junghye Lee*, Jimeng Sun, Fei Wang, Shuang Wang, Chi-Hyuck Jun, and Xiaoqian Jiang, "Privacy-preserving patient similarity learning in a federated environment", Journal of Medical Internet Research Medical Informatics, 6(2), April 2018. (selected in the 2019 edition of the Yearbook as one of the top 3 best articles out of 1,480 papers (0.2%) published in 2018 regarding ‘AI in Health: New Opportunities, Challenges, and Practical Implications’ link)

32. Miae Kim†, Junghye Lee†, and Jungho Im*, "Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data", GIScience & Remote Sensing, April 2018.

33. Kyeol Chang, Junghye Lee*, Chi-Hyuck Jun, and Hoeil Chung*, "Interleaved Incremental Association Markov Blanket as a potential feature selection method enabling of improving accuracy of near-infrared spectroscopic analysis", Talanta, 178, 348-354, February 2018.

Before 2018

34. Junghye Lee, Wonji Lee, Il-su Park, Hun-Sung Kim, Hyeseon Lee, and Chi-Hyuck Jun*, "Risk assessment for hypertension and hypertension complications incidences using a Bayesian network", IISE Transactions on Healthcare Systems Engineering, 6(4), 246-259, October 2016.

35. Kyeol Chang, Junghye Lee, Chi-Hyuck Jun, and Hoeil Chung*, "Acquisition of a series of temperature-varied sample spectra to induce characteristic structural changes of components and selection of target-descriptive variables among them for multivariate analysis to improve accuracy", Applied Spectroscopy Reviews, 51(7-9), 718-734, May 2016.

36. Junghye Lee, Kyeol Chang, Chi-Hyuck Jun, Rae-Kwang Cho, Hoeil Chung*, and Hyeseon Lee*, "Kernel-based calibration methods combined with multivariate feature selection to improve accuracy of near-infrared spectroscopic analysis", Chemometrics and Intelligent Laboratory Systems, 147, 139-146, October 2015.

37. Junghye Lee and Chi-Hyuck Jun*, "Classification of high dimensionality data through feature selection using Markov blanket", Industrial Engineering & Management Systems, 14(2), 210-219, June 2015.

38. Su-Dong Lee, Junghye Lee, and Chi-Hyuck Jun*, "Causality analysis for public and private expenditures on health using panel Granger-causality test", Industrial Engineering & Management Systems, 14(1), 104-109, March 2015.

39. Wonji Lee, Junghye Lee, Hyeseon Lee, Chi-Hyuck Jun, Il-su Park, and Sung-Hong Kang*, "Prediction of hypertension complications risk using classification techniques", Industrial Engineering & Management Systems, 13(4), 449-453, December 2014.