Nguyễn Thị Hồng Nhung



Hong – Nhung Nguyen received  a B.S. degree in information technology and master’s degree in software engineering from Hanoi National University (HVNU), Hanoi, Vietnam, in 2015 and 2018, respectively. In 2015, She spent nearly a year being an intern and working as a software engineer at NTT Data Vietnam. Since 2016, She works as a lecturer at the Faculty of Information Technology at Viet Tri Industry University, Viet Nam. In February 2023, She completed her D.Phil from the Infomation Technology Convergence lab in the Department of Electronic Engineering, Myongji University (MJU), Korea. Form April 2024, She has become an assistant professor at Department of Afftificial Intelligence and Software Engineering, Gachon University, South Korea. Her favorite research interests are machine learning and its applications in security, healthcare and some applications of machine learning in software engineering.


  • Automation Software Testing
  • Web & Mobile app technology
  • Artificial Intelligence in Healthcare
  • Machine Learning in Cyber Security


  • BS in Information Technology(2011), University of Engineering And Technology (UET), Vietnam National University,Hanoi(HVNU)
  • Title of Thesis: “Automation Testing with Sikuli”.
  • MS in Software Engineering (2016), University of Engineering And Technology (UET), Vietnam National University,Hanoi(HVNU)
  • Title of Thesis: “The research on generating automation testing code based on Behavior Driven Testing Scenario”.
  • PhD in Engineering(2020), MyongJi University, South Korea
  • Title of Thesis: “Artificial Intelligence in Cyber Security for Smart Grid”.


  • A Novel Two-Stage Deep Learning Model for Network Intrusion Detection: LSTM-AE Vanlalruata Hnamte, Hong Nhung – Nguyen , Jamal HussainYong, Yong-Hwa Kim IEEE Access (ISI) . (2023)
  • Generative Adversarial Network-Based Network Intrusion Detection System for Supervisory Control and Data Acquisition System Hong Nhung-Nguyen Sugwon Hong, Young-Woo Youn, Yong-Hwa Kim Energyunder review.
  • Machine-Learning Based Anomaly Detection for GOOSE in Digital Substations, H. Nhung-Nguyen , M. Girdhar, Y.-H. Kim, and J. Hong, IEEE Access under review.
  • Deep-Learning Based Post-Event Analysis in PowerSystems, Junho Hong, Yong-Hwa Kim, Hong Nhung-Nguyen , Jaerock Kwon, Energy, ISSN 1996-1073 (ISI). (2022)
  • A deep neural network to identify Vacuum Degree based on Partial Discharge Measurement Hong Nhung-Nguyen ,Young-Woo Youn, Yong-Hwa Kim, IEEE Access ISSN 2169-3536 (ISI). (2022)
  • One-Shot Learning-Based Driver’s Head Movement Identification Using Millimeter-Wave Radar Sensor, Hong Nhung – Nguyen , Seongwook Lee, Tien Tung – Nguyen, Yong-Hwa Kim, IET radar, Sonar & Navigation, ISSN 1751-8792 (ISI). (2022)
  • Performance Evaluation of Downlink Multiple Users NOMA-enable UAV-aided Communication Systems over Nakagami-m Fading Environments,Thu Thuy – Dao Thi, Sang Quang Nguyen, Hong Nhung – Nguyen , Phu Xuan Nguyen , Yong-Hwa Kim IEEE Access ISSN 2169-3536 (ISI). (2021)
  • Semi-Supervised GAN for Road Structure Recognition of Automotive FMCW Radar Systems, The Duong -Do , Hong Nhung-Nguyen , Duc Anh Pham, Yong-Hwa Kim, 2021 IEEE RIVF International Conference on Computing and Communication Technologies (RIVF) , Ha noi, Viet Nam