Machine Learning for Communication

Publications

23. O. T. Baydas, A. S. Okcu, and O. B. Akan, "Graph-Localized Offline Federated Multi-Agent Reinforcement Learning for Wireless Networks," to appear in ICML AI4NextG Workshop: AI and ML for Next-Generation Wireless Communications and Networking, Seoul, South Korea, July 2026.

22. A. S. Okcu, O. T. Baydas, and O. B. Akan, "Certified Characterization of Privacy, Participation, and Convergence in Over-the-Air Federated Learning," to appear in ICML AI4NextG Workshop: AI and ML for Next-Generation Wireless Communications and Networking, Seoul, South Korea, July 2026.

21. X. Hu, J. Li, S. Zhang, S. Goetz, L. Picinali, O. B. Akan, and A. O. T. Hogg, "HRTFformer: A Spatially-Aware Transformer for Individual HRTF Upsampling in Immersive Audio Rendering," to appear in IEEE Transactions on Multimedia, 2026.

20. H. Cai, H. Wang, H. Dong, K. Li, and O. B. Akan, "Graph Representation-Based Model Poisoning on the Heterogeneous Internet of Agents," in Proc. 22nd International Wireless Communications & Mobile Computing Conference (IWCMC), Shanghai, China, June 2026.

19. O. T. Baydas and O. B. Akan, "Physics-Informed Score-Based Diffusion Model for Bio-Nano Communication Channels," in Proc. IEEE ICC 2026, Glasgow, UK, June 2026.

18. K. Li, Y. Liang, P. Lio, W. Ni, F. Dressler, J. Crowcroft, and O. B. Akan, "User Isolation Poisoning on Decentralized Federated Learning: An Adversarial Message-Passing Graph Neural Network Approach," IEEE Transactions on Neural Networks and Learning Systems, vol. 37, no. 6, pp. 2619-2633, June 2026

17. H. Cai, K. Li, H. Wang, H. Dong, Y. Li, F. Dressler, and O. B. Akan, "Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs", submitted to IEEE Transactions on Network Science and Engineering, May 2026.

16. O. T. Baydas and O. B. Akan, "Physics-Informed Neural Operators for Signal Modeling in Particle-based Communications," IEEE Transactions on NanoBioscience (Early Access), doi: 10.1109/TNB.2026.3693618, 2026.

15. O. T. Baydas and O. B. Akan, "Robust and Differentially Private Federated Learning via Over-the-Air Computation for Norm-Aligned Poisoning Attacks," April 2026.

14. D. Luan, C. Liang, J. Huang, Z. Lin, K. Meng, C.-X. Wang, J. Thompson, and O. B. Akan, "Hybrid Mamba-Attention Neural Architecture for Channel Estimation," submitted to IEEE Global Communications Conference (GLOBECOM), April 2026.

13. A. S. Okcu and O. B. Akan, "Physics-Informed Odor Source Localization with Molecular Communication," submitted to IEEE Transactions on Neural Networks and Learning Systems, March 2026.

12. X. Lan, X. Zhang, L. Zhang, Z. Ma, Q. Wang, and O. B. Akan, "A Sparse Bayesian Learning-Based OTFS Channel Estimation for 6G Wireless System," IEEE Wireless Communications Letters, vol. 15, pp. 805-809, January 2026.

11. W. Ni, K. Li, C. Li, X. Yuan, S. Li, S. Zou, S. S. Ahmed, D. Niyato, A. Jamalipour, F. Dressler, and O. B. Akan, "Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things," IEEE Internet of Things Journal, vol. 12, no. 22, pp. 46269-46293, November 2025.

10. J. Zheng, O. B. Akan, et al., "GradCAM-AE: A New Shield Defense against Poisoning Attacks on Federated Learning," ACM Transactions on Privacy and Security, vol. 28, no. 53, pp. 1-23, November 2025.

9. K. Li, O. B. Akan, et al., "Explainable Graph Attention-Driven Fairness Manipulation for Federated Learning in EdgeIoT," in Proc. IEEE/CIC International Conference on Communications in China, Shanghai, China, August 2025.

8. K. Li, Y. Liang, X. Yuan, W. Ni, J. Crowcroft, C. Yuen, and O. B. Akan, "A Novel Framework of Horizontal-Vertical Hybrid Federated Learning for EdgeIoT," IEEE Networking Letters, vol. 7, no. 2, pp. 83-87, June 2025.

7. O. T. Baydas and O. B. Akan, "Federated Learning for Terahertz Wireless Communication," 2025.

6. K. Li, J. Zheng, W. Ni, H. Huang, P. Liò, F. Dressler, and O. B. Akan, "Biasing Federated Learning With a New Adversarial Graph Attention Network," IEEE Transactions on Mobile Computing, vol. 24, no. 3, pp. 2407-2421, March 2025.

5. H. Cai, H. Dong, H. Wang, K. Li, and O. B. Akan, "Graph Representation-based Model Poisoning on Federated LLMs in CyberEdge Networks," submitted to IEEE Communications Magazine, 2025.

4. K. Li, Z. Zhang, A. Pourkabirian, W. Ni, F. Dressler, O. B. Akan, "Towards Resilient Federated Learning in CyberEdge Networks: Recent Advances and Future Trends", submitted to ACM Transactions on Intelligent Systems and Technology, 2025.

3. K. Li, A. Noor, W. Ni, E. Tovar, X. Fu, O. B. Akan, "Poisoning Federated Learning with Graph Neural Networks in Internet of Drones," IEEE International Conference on Computer Communications and Networks (ICCCN), 2024.

2. K. Li, J. Zheng, X. Yuan, W. Ni, O. B. Akan and H. V. Poor, "Data-Agnostic Model Poisoning Against Federated Learning: A Graph Autoencoder Approach," IEEE Transactions on Information Forensics and Security, vol. 19, pp. 3465-3480, February 2024.

1. K. Li, J. Zheng, X. Yuan, W. Ni, H. Huang, P. Lio, F. Dressler, and O. B. Akan, "E-GATE: Explainable Graph-based Fairness Attacks on Federated Learning-enabled EdgeIoT", 2024.