Dr. Xianping Wang

Dr. Xianping Wang   Assistant Professor of Computer Science

   Office: Science & Technology Building 210

   Phone: (910) 672-2147

   Email: xwang3@uncfsu.edu

   Personal Homepage: 

BIOGRAPHY

Dr. Xianping Wang held a Ph.D. in Computer Science. He has an extensive background spanning academic research, university teaching, and industrial innovation. He bridges the gap between theoretical excellence and practical application, bringing years of experience in developing cutting-edge technologies and mentoring the next generation of Cybersecurity engineers.

TEACHING INTERESTS

Artificial intelligence, machine learning, computer vision, and natural language processing
Computer and network security, ethical hacking, cryptography, and digital forensics
Data structures and algorithms, programming at all levels, and database systems

RESEARCH INTERESTS

Machine learning applications for cybersecurity automation in information systems, IoT and robotics
AI/ML-driven intelligent systems for IoT, information systems enhancement and robotics

RECENT PUBLICATIONS

Wang, X., El-Tawab, S., Alhafdhi, A., Almalag, M., & Olariu, S.. Toward probabilistic data collection in the NOTICE architecture. IEEE Transactions on Intelligent Transportation Systems, 17(12), 1–10.

Wang, X., Qiu, H., Shen, J., Chen, W., Choi, A., & Zhao, W. Defeating Multimodal Information Manipulation By A Web 3.0 Decentralized Identity (DID)-Based Accountability Framework, 2025 IEEE 6th Annual World AI IoT Congress (AIIoT), Seattle, WA, USA, May 2025.

Wang, X., Qiu, H., Shen, J., Chen, W., Choi, A., & Zhao, W. (2025). Multimodal Large Language Models in Language Education: Personalization, Scale, and Future Potential, 2025 IEEE 6th Annual World AI IoT Congress (AIIoT), Seattle, WA, USA, May 2025.

Wang, X., Qiu, H., Shen, J., & Chen, W. A survey on the cybersecurity of IoT from the perspective of SoC. In 2023 10th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 66–71).

Long, X.M , Wang, X., Calix, R. A., Kim, T.-H., & Jiang, K. (2021). Categorizing Chinese glyphs based on Liushu with convolutional neural networks. In 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) (pp. 0396–0401).