ITP Lab 2024 Annual Report

This year, the ITP Lab continues to demonstrate its leadership in research excellence and global engagement.

First, we are thrilled to share that Prof. Geoffrey Ye Li, the director, was elected as a Fellow of the Royal Academy of Engineering (FREng), Class of 2024, in recognition of his outstanding contributions to wireless signal processing, transmission, and standardization. In addition, Prof. Li received the 2024 IEEE Eric E. Sumner Award for his groundbreaking work on frequencydomain communications, including orthogonal frequency division multiplexing (OFDM). Moreover, he was also recognized as a 2024 World’s Most Influential Scientific Mind (i.e., Highly Cited Researcher) by Thomson Reuters, underscoring the far-reaching impact of his research.

Second, the ITP Lab played a central role in organizing reputed international  conferences. In September 2024, we successfully hosted the 2024 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2024) in London, UK, where Prof. Li served as General Co-Chair, Dr. Shixiong Wang as a Publicity Co-Chair, and Mr. Kaidi Xu as the Webmaster. Earlier in May, Prof. Li acted as the Technical Program Co-Chair for the 2024 IEEE International Conference on Machine Learning for Communications and Networking (ICMLCN 2024) in Stockholm, Sweden. Looking ahead, Prof. Li has been appointed as General Co-Chair for the upcoming 2025 IEEE Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC 2025) to be held in Surrey, UK.

Third, the ITP Lab consistently achieves significant advancements in research productivity, with 9 first-authored papers [1]-[9] and over 25 coauthored papers published in leading journals such as IEEE Transactions on Wireless Communications, IEEE Communications Magazine, IEEE Transactions on Signal Processing, IEEE Transactions on Pattern Analysis and Machine Intelligence, and Mathematics of Operations Research. We also contribute to international conferences, presenting 6 first-authored papers [10]-[15] and 2 coauthored papers at reputed events, including the 2024 IEEE Vehicular Technology Conference (VTC 2024), 2024 IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2024), 2024 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2024), and 2025 IEEE Conference on Computer Communications (INFOCOM 2025), etc. In addition, several first-authored preprints have been published on ArXiv.

Fourth, the laboratory invited five prominent scholars to deliver talks, including Prof. Christos Masouros (University College London), Prof. Shenglong Zhou (Beijing Jiaotong University), Prof. Wei Zhang (University of New South Wales), Prof. Wei Yu (University of Toronto), and Prof. Zhu Han (University of Houston). These interactions enriched the ITP Lab’s intellectual ecosystem and fostered collaborative opportunities.

Fifth, the laboratory welcomed two new postdoctoral researchers, Dr. Jingzhi Hu and Dr. Zhenzi Weng, who bring fresh perspectives to the vibrant research environment of the ITP Lab. Additionally, the lab hosted two visiting students, Mr. Jiawei Cao from the University of Electronic Science and Technology of China, from December 2023 to June 2024, and Ms. Shan Sha from Beijing Jiaotong University, from December 2023 to December 2024, further enhancing its international reach and influence. As the year concludes, the ITP Lab reflects with pride on its achievements and looks forward to continuing its mission of advancing knowledge in signal processing and machine learning for wireless communications. The dedication and contributions of its members ensure that it remains at the forefront of innovation and excellence.  

A detailed Lab Annual Report can be found in ITP Lab 2024 Annual Report.

Reference List:

[1] Shixiong Wang and Geoffrey Ye Li, “Machine learning in communications: A road to intelligent transmission and processing,” Communications of Huawei Research, Issue 7, pp. 2-20, October 2024. (Invited Article.)
[2] Shixiong Wang, Wei Dai, Haowei Wang, and Geoffrey Ye Li, “Robust waveform design for integrated sensing and communication,” IEEE Transactions on Signal Processing, vol. 72, no. 7, pp. 3122-3138, July 2024.
[3] Shenglong Zhou, Lili Pan, Naihua Xiu, and Geoffrey Ye Li, “A 0/1 Constrained Optimization Solving Sample Average Approximation for Chance Constrained Programming.” Mathematics of Operations Research, Early Access, October 2024.
[4] Kaidi Xu, Shenglong Zhou, Geoffrey Ye Li, “Federated reinforcement learning for resource allocation in V2X networks,” to appear in IEEE Journal of Selected Topics in Signal Processing, 2024.
[5] Kaidi Xu, Shenglong Zhou, Geoffrey Ye Li, “Rescale-invariant federated reinforcement learning for resource allocation in V2X networks,” to appear in IEEE Communications Letters, 2024.
[6] Yanzhen Liu, Zhijin Qin, and Geoffrey Ye Li, “Energy-efficient distributed spiking neural network for wireless edge intelligence,” IEEE Transactions on Wireless Communications, vol. 23, no. 9, pp. 10683-10697, September 2024.
[7] Bowen Zhang, Zhijin Qin, and Geoffrey Ye Li. “Compression ratio learning and semantic communications for video imaging,” IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 3, pp. 312-324, April 2024.
[8] Houssem Sifaou and Geoffrey Ye Li, “Over-the-air federated learning over scalable cellfree massive MIMO,” IEEE Transactions on Wireless Communications, vol. 23, no. 5, pp. 4214-4227, May 2024.
[9] Jiawei Cao, Chongtao Guo, Hao Li, Zhigang Wang, Houjun Wang, and Geoffrey Ye Li, “Deep learning-based performance testing for analog integrated circuits,” IEEE Transactions on Very Large Scale Integration Systems, Early Access, November 2024.
[10] Kaidi Xu, Shenglong Zhou, Geoffrey Ye Li, “Federated reinforcement learning for resource allocation in V2X networks,” Proc. 2024 IEEE 99th Vehicular Technology Conference, Singapore, June 2024.
[11] Kaidi Xu, Shenglong Zhou, Geoffrey Ye Li, “Communication-efficient decentralized federated learning via one-bit compressive sensing,” Proc. 2024 IEEE 99th Vehicular Technology Conference, Singapore, June 2024.
[12] Bowen Zhang, Zhijin Qin, and Geoffrey Ye Li, “Spectral and spatial transformer for multitarget estimation in ISAC,” Proc. 2024 IEEE 35th Annual International Symposium on Personal, Indoor and Mobile Radio Communications, Valencia, Spain, September 2024.
[13] Shixiong Wang, Wei Dai, and Geoffrey Ye Li, “Distributionally robust outlier-aware receive beamforming,” Proc. IEEE International Workshop on Machine Learning for Signal Processing (MLSP), London, UK, September 2024.
[14] Tianxin Wang, Shuo Wang, Xudong Wang, and Geoffrey Ye Li, “Collaborative learning for less online retraining of neural receivers,” Proc. IEEE International Workshop on Machine Learning for Signal Processing (MLSP), London, UK, September 2024.
[15] Tianxin Wang, Xudong Wang, and Geoffrey Ye Li, "GraphRx: Graph-based collaborative learning among multiple cells for uplink neural receivers," accepted by 2025 IEEE Conference on Computer Communications (INFOCOM), December 2024.