李洋，助理教授，哲学博士学位（电脑科学），毕业于澳门大学智慧城市物联网国家重点实验室。主要从事人工智能专业的科研和教学工作，研究方向主要有云边协同智能、语义通信、强化学习等。在移动计算顶级期刊TMC、无线通信顶级期刊TWC、大数据顶级期刊TBD、网络科学与工程期刊TNSE、可持续计算期刊等国际一流期刊和会议上发表论文15余篇。发表在大数据TBD期刊论文为高被引论文，且获得2023年广东省计算机协会优秀论文奖。发表在国际无线通信与光纤会议论文，获得了2022年第31届Charles Kao最佳会议论文奖，担任多个国际会议的PC成员（Infocom、GlobalCom、MSN、ICC、VTC）和国际期刊的审稿人（TWC、TCOM、TNSE、TVT、IoTJ、ChinaCom等）。目前，主持教育部海外引才项目，四川省自然科学青年基金，以及中央高校基本科研项目，参与多个国家自然科学面上项目、国家重点及地区联合项目等。
谷歌学术主页：https://scholar.google.com.hk/citations?user=TZ9xBoYAAAAJ&hl=zh-CN.
代表性论文：
Yang Li, Y. Xue, J. Zeng, D. Zheng, L. Feng, and H. Xing, "Collaborative Transformer Inference in Multi-Tier Multi-Node Edge Networks," IEEE Network, 2026, doi: 10.1109/MNET.2026.3651817. (SCI一区)
J. Zeng, G. Zhang, Y. Li*, J. Zhou, T. Wang, and W. Jia, "Cloud-edge Collaboration for Robust Network Embeddings," ACM Transactions on Internet Technology, Just Accepted (March 2026). (CCF-B, SCI一区)
Yang Li, C. Dou, Y Wu, W. Jia, and R. Lu, "NOMA Assisted Two-Tier VR Content Transmission: A Tile-Based Approach for QoE Optimization," IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 3769-3784, May 2024. (CCF-A, SCI一区)
Yang Li, Y. Wu, Y. Song, L. Qian and W. Jia, “Dynamic User-Scheduling and Power Allocation for SWIPT Aided Federated Learning: A Deep Learning Approach,” IEEE Transactions on Mobile Computing, vol. 22, no. 7, pp. 4296-4312, 2023. (CCF-A, SCI一区)
Yang Li, Y. Wu, M. Dai, B. Lin, W. Jia, and X. Shen, “Hybrid NOMA-FDMA Assisted Dual Computation Offloading: A Latency Minimization Approach,” IEEE Transactions on Network Science and Engineering, vol. 9, no. 5, pp.3345-3360, 2022. (SCI一区)
Yang Li, T. Wang, Y. Wu, and W. Jia “Optimal dynamic spectrum allocation assisted latency minimization for multiuser mobile edge computing,” Digital Communications and Networks, vol. 8, no.3, pp 274-256, 2022. (SCI一区)
Yang Li, Y. Wu, S. Bi, L. Qian, Tony Q. S. Quek, C. Xu and Z. Shi, “Two-Tier Multi-Access Partial Computation Offloading via NOMA: A Hybrid Deep Learning Approach for Energy Minimization,” 2022 31st Wireless and Optical Communications Conference (WOCC), 2022, pp. 138-143. (最佳论文奖)
招生：课题组氛围轻松人性化，跟着导师步伐走无毕业压力，欢迎自身积极性强、代码和数学基础好、且努力勤奋的同学加入，咨询请发邮件到liyang23@swjtu.edu.cn.
