(*corresponding author, † equal contribution)

2025 

1. 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" (accepted at Expert Systems with Applications).

2. Hyerim Park†, Wonho Sohn†, Eunjin Kang, Jungho Im, and Junghye Lee*, "Developing a Novel Temporal Air-quality Risk Index Using LSTM Autoencoder: A Case Study with South Korean Air Quality Data" (accepted at Science of The Total Environment).

2024

3. Seok-Ju Hahn, Gi-Soo Kim*, and Junghye Lee*, "Pursuing Overall Welfare in Federated Learning through Sequential Decision Making", The 41st International Conference on Machine Learning (ICML), July, 2024. 

4. Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang, Junghye Lee, and Seulki Lee*, "CAFO: Feature-Centric Explanation on Time Series Classification", The 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Aug 2024.

5. 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",  IEEE Access, 2024.

6. 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

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

8. Wonho Sohn†, Dongcheol Lim, Suhyeon Kim*, and Junghye Lee*, "Inter-country Trade Similarity Graph-based Long Short-Term Memory for Port Throughput Prediction" (under revision at Engineering Applications of Artificial Intelligence).

9. Hyewon Kang†, Taek-Ho Lee†, and Junghye Lee*, "RP-GCN: A recurrence plot based graph convolutional network for time series classification" (under revision at Applied Intelligence).

10. Suhyeon Kim†, Taek-Ho Lee†, and Junghye Lee*, "Exploiting Graph Structures for Time Series Forecasting with Graph Representation Learning" (submitted to Neurocomputing).

11. Wonho Sohn†, Suhyeon Kim†, Dongcheol Lim, Hyerim Park, and Junghye Lee*, "MDL-FR: Multi-modal Deep Learning-based Fashion Recommendation with Styles" (submitted to Engineering Applications of Artificial Intelligence).

12. MyoungHoon Lee and Junghye Lee*, "FT-MixE: Fourier Transform-based Mixing of Knowledge Graph Embeddings for Efficient and Enhanced Link Prediction" (submitted to IEEE Transactions on Knowledge and Data Engineering).

13. Dongcheol Lim, Suhyeon Kim*, and Junghye Lee*, "An Explainable Supervised Deep Learning Model with Risk Score for Biological Age Estimation" (submitted to Artificial Intelligence in Medicine).

14. Hyerim Park†, Sean-Daniel Buddingh†, Eunbi Jeon, and Junghye Lee*, "Exploiting Latent Contextual Knowledge for High-Performance Lightweight Large Language Models: A Framework for Children’s Language" (submitted to Information Sciences).

2023

15. 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.

16. 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.

17. 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.

18. 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.

19. 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

20. 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])

21. 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.

22. 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.

23. 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.

24. 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.

25. 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

26. 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.

27. 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.

28. 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.

29. 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.

30. 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

31. 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.

32. 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.

33. 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

34. 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

35. 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. 

36. 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.

37. 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.

38. 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)

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

40. 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

41. 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.

42. 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.

43. 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.

44. 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.

45. 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.

46. 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.