Jing Li

Dr. Li Jing is an Assistant Professor in the School of Computing and Data Science at Xiamen University Malaysia. He holds a PhD in Informatics Engineering and brings academic and industry experience across China, the United States, and Malaysia.

His research focuses on AI-driven cyber defense, trustworthy AI, secure agentic systems, agentic cybersecurity operations, and IoT, edge, and cyber-physical security. His work connects machine-learning-based threat detection with explainable evidence, secure agent architectures, and human-supervised cyber defense, with attention to robustness, privacy, continual learning, and accountable action.

His broader interests include artificial intelligence, computer networking, IoT, cybersecurity, digital twins, and large language model applications. At Xiamen University Malaysia, he teaches data management and AI, computer networks, network traffic analysis, advanced network attack and defense, and biometrics.

• Merit Thesis Award Honorary Doctoral Thesis Award, 2025
• Certificate of Excellence Doctoral Thesis Top B1, 2025
• UTM Web of Science Q1 Academic Paper Scholarship, 2024-2025
• UTM Postgraduate Annual Research Seminars (PARS) Committee, 2024-2025
• International Doctoral Fellowship (IDF) at UTM, 2023-2024
• Asian Youth Leaders Scholarship Award, 2024
• Best Researcher (10588), The 21st Edition of International ACADEMIC AWARDS, 2024
• Best Paper (2682), The 17th Edition of International Research Awards on Cybersecurity And Cryptography, 2024
• Academic Visit at the University of Dubai, 2024
• Big Data, AI-SLR Series Course Professor Assistant at UTM, 2023-2024
• Elite Global Excellence Committee Technical Team Member, 2023-2024

• Selected publications (full list on my academic website in the Websites section)
  
  SIFT-IDS: Sparse Iterative Feature Tuning for In-Vehicle Intrusion Detection. C. Wang, J. Li et al. AITC, 38–44, 2026. DOI: 10.1109/AITC70732.2026.11666574
  
  NFIoT-GATE-DTL IDS: Genetic algorithm-tuned ensemble of deep transfer learning for NetFlow-based intrusion detection system for internet of things. J. Li et al. Engineering Applications of Artificial Intelligence, 143, 110046, 2025. DOI: 10.1016/j.engappai.2025.110046
  
  Adaptive NetFlow IIoT Intrusion Detection with Deep Transfer Learning, Genetic Optimization, and Ensemble Methods for Network Management. J. Li et al. IEEE TNSM, 2025. DOI: 10.1109/TNSM.2025.3617765
  
  IoT security: a systematic literature review of feature selection methods for machine learning-based attack classification. J. Li et al. IJESDF, 2025. DOI: 10.1504/IJESDF.2025.143475
  
  Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning. J. Li et al. Journal of Big Data, 11, 36, 2024. DOI: 10.1186/s40537-024-00892-y
  
  Enhancing IoT security: A comparative study of feature reduction techniques for intrusion detection system. J. Li et al. Intelligent Systems with Applications, 23, 200407, 2024. DOI: 10.1016/j.iswa.2024.200407
  
  A critical review of feature selection methods for machine learning in IoT security. J. Li et al. IJCNDS, 30, 2024. DOI: 10.1504/IJCNDS.2024.138214
  
  Cybersecurity Insights: Analyzing IoT Data Through Statistical and Visualization Techniques. J. Li et al. PCDS, 2024. DOI: 10.1109/PCDS61776.2024.10743769

Assistant Professor, School of Computing and Data Science, Xiamen University Malaysia.

Courses taught:
G0336 — Data Management and Artificial Intelligence
CST309 — Computer Networks and Communication
CYS304 — Network Traffic Monitoring and Analysis
CYS306 — Advanced Network Attack and Defence Technology
CYS402 — Biometrics

Research directions:
AI-driven cyber threat detection; trustworthy AI and AI security; secure and trustworthy agentic AI; agentic AI for cybersecurity operations; intelligent IoT, edge and cyber-physical security.

Student research includes SIFT-IDS (AITC 2026) and the ACM CCS 2026 poster ROS2Pot: An Agentic Honeypot for Proactive Defense Against LLM Agents in ROS 2/DDS Systems, by Yucheng Zheng, Jing Li and Wei-Chuen Yau (November 15–19, 2026). DOI: 10.1145/3830454.3846411.

Research conversations and collaboration: jing.li@xmu.edu.my

• PhD, University Technology Malaysia, Malaysia
• Master, Zhejiang University, Hangzhou, China
• Bachelor, China Jiliang University, Hangzhou, China

• Academic guidance of experiment activities and scientific paper writing for undergraduate and graduate students in computer science and management.
  PhD application guidance covers the whole process from research proposal to university and supervisor exploration, application, and interview to help students successfully become PhD students.
  Active on social media, ”门童靖博士” in WeChat with 5000+ fans and Zhihu with 1000+ fans.
  Active Clubs: Zhejiang University's official entrepreneurship club, football club, reading club, and Chinese tea club.
  Swimming Coach, National Swim Lifeguard (Level 5), General Administration of Sport, China. Crossing Hangzhou Qiantang River 2018, 2020, 2021.
  
  Books and other writing:
  Feature Selection and Feature Extraction in Machine Learning-Based IoT Intrusion Detection System: Optimizing IoT Classification Models. Jing Li and Hewan Chen. Eliva Press, 2024. ISBN 9999317790.
  ChatGPT技术与伦理相关问题的思考. 中国计算机学会通讯, 19(9), 2023.
  Authoritative Guide to Wi-Fi Networks. Xidian University Press. ISBN 978-7-5606-4784-5. First author.