Ph.D. in Electrical and Computer Engineering
University of Dayton, Dayton, Ohio
Biography
I am an Assistant Professor of Computer Science at La Sierra University. I received my Ph.D. in Electrical and Computer Engineering from the University of Dayton.
My research focuses on secure and intelligent networking, with an emphasis on AI-driven network traffic analysis, intrusion detection, and resilient wireless, edge, and Industrial Internet of Things systems.
I develop lightweight and trustworthy machine learning methods that operate under limited computation, bandwidth, and labeled data while maintaining security and predictive performance. My current work explores federated learning, cross-domain adaptation, retrieval-augmented generation, and synthetic data generation for cybersecurity applications.
Research interests
- Network Security
- Next-Generation Networking
- Wireless Communications
- Internet of Things
- Artificial Intelligence
Academic appointment
Assistant Professor
Department of Computer Science
La Sierra University
Riverside, California
Background
Education
M.S. in Electrical and Computer Engineering
University of Dayton, Dayton, Ohio
B.S. in Automation
Dalian Jiaotong University, Dalian, China
Recognition
Honors & Awards
U.S. Department of Energy Genesis Mission Research Award
U.S. Department of Energy
Schrillo Faculty Research Grant Award
La Sierra University
Best Paper Award
IEEE Cyber Awareness and Research Symposium (CARS)
Research output
Recent Publications
Selected representative work.
- C. Stolz, D. P. Fiadzeawu, J. Zhang, S. Sullivan, and F. Li, “RCS-Fed: Rare-Class Contribution Scoring for Federated Intrusion Detection in IIoT,” IEEE World AI IoT Congress (AIIoT), 2026.
- A. Tiwari, S. Sullivan, C. Stolz, J. Zhang, F. Li, and E. Hwang, “A Deployable Platform for Real-World Network Traffic Classification Edge Devices,” IEEE CCWC, 2026.
- D. P. Fiadzeawu, L. V. Jabla, J. Zhang, and F. Li, “Beyond Accuracy: Fidelity Evaluation Framework for Synthetic Data in Network Intrusion Detection,” IEEE CCWC, 2026.
- I. Udoidiok, F. Li, and J. Zhang, “Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study,” Information, vol. 17, no. 1, 2025.
- M. Lei, J. Zhang, and F. Li, “Towards Prompt and Trustworthy SoH Monitoring for Safety-Critical Battery Systems,” IEEE CARS, 2025.
- J. Zhang and F. Li, “Model-Agnostic Unsupervised Detection of Prompt Injection with Multiscale Perplexity Signatures,” IEEE MILCOM, 2025.
- D. P. Fiadzeawu, J. Zhang, and F. Li, “MEFA: Multisource Entropy-Weighted Feature Adaptation for Cross-Domain Intrusion Detection,” Security and Privacy, vol. 8, no. 5, 2025.
- M. Lei, J. Zhang, and F. Li, “Unsupervised Domain Adaptation for SoC Prediction across SoH Conditions in LFP Batteries,” IEEE NAECON, 2025.
- J. Zhang, F. Li, H. Wu, and V. Kumar, “Clustering-Informed Retrieval-Augmented Generation for LLM-Based Log Anomaly Detection,” IEEE NAECON, 2025.
- F. Li, I. Udoidiok, and J. Zhang, “A Comprehensive Study on Lightweight Convolution Techniques for Malicious Traffic Synthesis in Diffusion Models,” IEEE Access, vol. 13, 2025.
Research
Interests
Secure & Trustworthy AI
Model resilience, federated learning, adversarial robustness, and prompt-injection detection.
Network Intelligence
Traffic classification, intrusion detection, and data-driven network management.
Edge & Wireless Systems
Lightweight learning for constrained, connected, and cyber-physical environments.
Generative Methods
Synthetic cybersecurity data, cross-domain adaptation, and retrieval-augmented generation.
Get in touch
Contact
I welcome conversations about research collaboration, student projects, and applied AI for secure networked systems.
fli@lasierra.edu