Private Federated Learning With Misaligned Power Allocation via Over-the-Air Computation. - Na Yan 002; Kezhi Wang; Cunhua Pan; Kok Keong Chai (IEEE Commun. Lett., 2022)

Performance Analysis for Channel-Weighted Federated Learning in OMA Wireless Networks. - Na Yan 002; Kezhi Wang; Cunhua Pan; Kok Keong Chai (IEEE Signal Process. Lett., 2022)

Device Scheduling for Over-the-Air Federated Learning with Differential Privacy. - Na Yan 002; Kezhi Wang; Cunhua Pan; Kok Keong Chai (ICC, 2023)

Over-the-Air Federated Averaging With Limited Power and Privacy Budgets. - Na Yan 002; Kezhi Wang; Cunhua Pan; Kok Keong Chai; Feng Shu 002; Jiangzhou Wang (IEEE Trans. Commun., 2024)

Device Scheduling for Secure Aggregation in Wireless Federated Learning. - Na Yan 002; Kezhi Wang; Kangda Zhi; Cunhua Pan; Kok Keong Chai; H. Vincent Poor (IEEE Internet Things J., 2024)

Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences. - Adnan Shahid; Adrian Kliks; Ahmed Al-Tahmeesschi; Ahmed Elbakary; Alexandros Nikou; Ali Maatouk; Ali Mokh; Amirreza Kazemi; Antonio De Domenico; Athanasios Karapantelakis; Bo Cheng 001; Bo Yang 035; et al. (CoRR, 2025)

Secure and Private Over-the-Air Federated Learning: Biased and Unbiased Aggregation Design. - Na Yan 002; Kezhi Wang; Kangda Zhi; Cunhua Pan; Kok Keong Chai; H. Vincent Poor (IEEE Trans. Wirel. Commun., 2025)