전임교수

Technology Management, Economics and Policy Program
이정혜 교수 사진
이정혜 교수
Junghye Lee

연구분야

  • Privacy-preserving Machine Learning
  • Federated Learning
  • Graph Machine Learning
  • Smart Healthcare
  • Smart Manufacturing
  • Technology Management

학력

  • B.S. (2012) Industrial and Management Engineering, POSTECH
  • Ph.D. (2017) Industrial and Management Engineering, POSTECH

경력

  • 2023.3 ~ 현재 : 서울대학교 공학전문대학원 & 공과대학 기술경영경제정책 협동과정 조교수
  • 2022.3 ~ 2023.2 : 울산과학기술원 산업공학과 (인공지능대학원 겸임) 부교수
  • 2018.3 ~ 2022.2 : 울산과학기술원 산업공학과 조교수
  • 2017.8 ~ 2018.2 : UC San Diego, School of Medicine, Department of Biomedical Informatics 연구원

주요 논문

  1. 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, March 2024. (SCI(E))
  2. 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, December 2023. (SCI(E))
  3. 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, August 2023. (SSCI)
  4. 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. (SCI(E))
  5. 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, June 2023. (SCI(E))
  6. 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 Transaction, September 2023. (SCI(E))
  7. 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, December 2022. (SCI(E))
  8. 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. (SCI(E))
  9. 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. (Top Conference)
  10. 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. (SSCI)
  11. YongKyung Oh, Chiehyeon Lim, Junghye Lee, Sewon Kim, and Sungil Kim*, "Multichannel Convolution Neural Network for Gas Mixture Classification", Annals of Operations Research, April 2022. (SCI(E))
  12. 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. (SCI(E))
  13. 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. (SCI(E))
  14. 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. (SCI(E))
  15. 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. (SCI(E))
  16. 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. (SCI(E))


서울대학교 대학원 협동과정 기술경영경제정책전공