Dr. Ting Li | Fault prediction | Best Researcher Award 

Researcher and Lecturer, Guangxi University, China

Dr. Ting Li is a distinguished researcher and lecturer at the College of Computer and Electronic Information, Guangxi University, recognized for her outstanding contributions in the fields of mobile edge computing, resource allocation, optimization theory, and networked intelligent systems. She earned her Doctor of Philosophy (Ph.D.) in Cyberspace Security from the Institute of Information Engineering, Chinese Academy of Sciences, where she focused on developing intelligent, secure, and privacy-aware computational frameworks that address real-world challenges in edge computing environments. Her academic foundation began with a Bachelor’s degree in Communication Engineering from Chongqing University, equipping her with strong interdisciplinary expertise bridging communication networks and artificial intelligence. Since joining Guangxi University as a lecturer, Dr. Ting Li has been actively involved in teaching, mentoring, and research, leading and participating in several high-impact projects funded by the National Natural Science Foundation of China and the National Key R&D Program, focusing on cross-modal recognition, task offloading, and secure data processing for IoT systems. Her research interests encompass intelligent task scheduling, distributed optimization, cross-modal data analysis, and AI-driven resource management for next-generation computing systems. Dr. Ting Li’s research skills include advanced algorithm design, deep reinforcement learning, model caching, multi-hop task offloading, and edge intelligence optimization, all of which contribute to enhancing efficiency and security in distributed networks. Her publications in world-renowned journals such as IEEE Transactions on Mobile Computing, IEEE Transactions on Parallel and Distributed Systems, IEEE Communications Letters, and IEEE Internet of Things Journal have established her as an influential scholar in AI-powered edge computing research. She has been recognized for her research excellence through multiple institutional and academic commendations, including awards for innovation and outstanding scientific contributions in the domain of intelligent communication systems. Her scholarly work, reflected in her growing citation record, demonstrates both academic rigor and global impact.

Profiles: Google Scholar

Featured Publications

• Li, T., Liu, Y., Ouyang, T., Zhang, H., Yang, K., & Zhang, X. (2025). Multi-hop task offloading and relay selection for IoT devices in mobile edge computing. IEEE Transactions on Mobile Computing, 24(1), 466–481. Cited by: 13

• Li, T., Sun, J., Liu, Y., Zhang, X., Zhu, D., Guo, Z., & Geng, L. (2023). ESMO: Joint frame scheduling and model caching for edge video analytics. IEEE Transactions on Parallel and Distributed Systems, 34(8), 2295–2310. Cited by: 10

• Zhu, D., Liu, H., Li, T., Sun, J., Liang, J., Zhang, H., & Geng, L. (2021). Deep reinforcement learning-based task offloading in satellite-terrestrial edge computing networks. IEEE Wireless Communications and Networking Conference (WCNC), 1–7. Cited by: 63

• Zhu, D., Li, T., Tian, H., Yang, Y., Liu, Y., Liu, H., Geng, L., & Sun, J. (2021). Speed-aware and customized task offloading and resource allocation in mobile edge computing. IEEE Communications Letters, 25(8), 2683–2687. Cited by: 17

• Li, T., Liu, H., Liang, J., Zhang, H., Geng, L., & Liu, Y. (2020). Privacy-aware online task offloading for mobile-edge computing. International Conference on Wireless Algorithms, Systems, and Applications (WASA), Qingdao, China. Cited by: 12