教师简介

吴加其，男，广东中山人，工学博士，毕业于哈尔滨工业大学（深圳）信息与通信工程专业

联系方式

47-392@gduf.edu.cn

主讲课程

人工智能、机器学习、数据挖掘、程序设计基础

研究方向

通信网络优化，强化学习，边缘智能，生成式人工智能，大语言模型

主要科研成果

期刊论文

[1] J. Wu, X. Zhuang, M. Tang and L. Gao, "QoE-Aware Offloading and Resource Allocation for MEC-Empowered AIGC Services," IEEE Transactions on Mobile Computing, vol. 24, no. 10, pp. 9664-9682, Oct. 2025.

[2] J. Wu, J. Luo, C. Jiang and L. Gao, "A Multiagent Deep Reinforcement Learning Approach for Multi-UAV Cooperative Search in Multilayered Aerial Computing Networks," IEEE Internet of Things Journal, vol. 12, no. 5, pp. 5807-5821, Mar. 2025.

[3] J. Wu, M. Tang, C. Jiang, L. Gao and B. Cao, "Cloud-Edge-End Collaborative Task Offloading in Vehicular Edge Networks: A Multilayer Deep Reinforcement Learning Approach," IEEE Internet of Things Journal, vol. 11, no. 22, pp. 36272-36290, Nov. 2024.

[4] H. Liu, J. Wu, Z. Wang, B. Cao and L. Gao, "Joint Edge Server Deployment and Computation Offloading: A Multi-Timescale Stochastic Programming Framework," IEEE Transactions on Mobile Computing, vol. 25, no. 4, pp. 4535-4550, Apr. 2026.

[5] H. Liu, X. Zhuang, J. Wu, Y. Luo, B. Cao and L. Gao, "Joint Communication and Computation Scheduling for MEC-enabled AIGC Services: A Game-Theoretic Stochastic Learning Approach," IEEE Internet of Things Journal, Early Access.

会议论文

[6] J. Wu, J. Luo, C. Jiang and L. Gao, "Multi-UAV Cooperative Search in Multi-Layered Aerial Computing Networks: A Multi-Agent Deep Reinforcement Learning Approach," IEEE International Conference on Communications (ICC), Denver, CO, USA, 2024.

[7] J. Wu, J. Luo, T. Wang and L. Gao, "Joint Optimization of Flying Trajectory and Task Offloading for UAV-Enabled MEC Networks: A Digital Twin-Assisted Hybrid Learning Approach," IEEE Vehicular Technology Conference (VTC-Spring), Singapore, Singapore, 2024.

[8] J. Wu, Z. Ye, L. He, T. Wang and L. Gao, "A Multi-Layer Deep Reinforcement Learning Approach for Joint Task Offloading and Scheduling in Vehicular Edge Networks," IEEE International Conference on Communications (ICC), Rome, Italy, 2023.

[9] J. Wu, H. Lin, H. Liu and L. Gao, "A Deep Reinforcement Learning Approach for Collaborative Mobile Edge Computing," IEEE International Conference on Communications (ICC), Seoul, Korea, 2022.

[10] R. Tian, J. Wu, J. Luo, Z. Wang and L. Gao, "Joint Observation and Transmission Scheduling for Satellite Networks with Heterogeneous Missions," IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, 2025.

[11] X. Zhuang, J. Wu, H. Wu, M. Tang and L. Gao, "QoS-Driven Hybrid Inference Scheme for Generative Diffusion Models in MEC-Enabled AI-Generated Content Networks," IEEE International Conference on Communications (ICC), Montreal, Canada, 2025.

[12] X. Zhuang, J. Wu, H. Wu, T. Zhang and L. Gao, "Joint Optimization of Model Inferencing and Task Offloading for MEC-Empowered Large Vision Model Services," IEEE Conference on Computer Communications (INFOCOM), London, United Kingdom, 2025.

[13] H. Liu, J. Wu, X. Zhuang, H. Wu and L. Gao, "Joint Communication and Computation Scheduling for MEC-Enabled AIGC Services Based on Generative Diffusion Model," International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Seoul, Korea, 2024.