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Publications

  1. Jaikhow, O., Sureephong, P., Chernbumroong, S., Sakarinkhul, P., Silapawetin, P. (2026). Development of an Exercise Monitoring Dashboard Using RAD and JAD Methodologies. 2026 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunication Engineering (ECTI DAMT & NCON). https://doi.org/10.1109/ECTIDAMTNCON67592.2026.11460033

  2. Bai, Y., Xie, B., Liu, Y., Chang, Z., Jäntti, R. (2025). Dynamic UAV Deployment in Multi-UAV Wireless Networks: A Multimodal-Feature-Based Deep Reinforcement Learning Approach. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2025.3556300

  3. Luan, M., Chang, Z., Mumtaz, S., Min, G., Hämäläinen, T. (2025). End-Edge Collaborative Control for AoI-Aware Short-Packet Industrial Cyber-Physical System. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/JSAC.2025.3574617

  4. He, H., Gu, Y., Hu, Y., Fang, F., Ning, X., Chen, X., Cheng, L. (2025). Real-time workflow scheduling in hybrid clouds with privacy and security constraints: A deep reinforcement learning approach. Expert Systems with Applications, 278, 127376. https://doi.org/10.1016/j.eswa.2025.127376

  5. Yu, L., Chang, Z., Jia, Y., Min, G. (2025). Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2025.3554247

  6. Wan, F., Wang, K., Wang, T., Qin, H., Fondrevelle, J., Duclos, A. (2025). Enhancing healthcare resource allocation through large language models. Swarm and Evolutionary Computation, 94, 101859. https://doi.org/10.1016/j.swevo.2025.101859

  7. Huang, T., Liu, J., Chang, Z., Wei, Y., Zhao, X., Liang, Y.-C. (2025). Energy Efficient Spectrum Sharing and Resource Allocation for 6G Air-Ground Integrated Networks. IEEE Transactions on Network and Service Management. https://doi.org/10.1109/TNSM.2025.3527651

  8. Wan, F., Wang, T., Wang, K., Si, Y., Fondrevelle, J., Du, S., Duclos, A. (2025). Surgery scheduling based on large language models. Artificial Intelligence in Medicine, 166, 103151. https://doi.org/10.1016/j.artmed.2025.103151

  9. Athama, A., Srivastava, A., Huang, S., Wang, K., Li, Y., Zhai, X. (2025). Wireless Single-Camera Markerless Motion Capture System for Healthcare Applications. 2025 IEEE International Conference on High Performance Computing and Communications (HPCC). https://doi.org/10.1109/HPCC67675.2025.00106

  10. Jin, C., Luan, M., Chang, Z., Hu, F., Pölönen, I., Liang, Y.-C. (2025). Secure Transmission for Integrated Backscatter Networks: A QoS-Guaranteed Multi-Device Scheduling and Time Switching Strategy. IEEE Transactions on Communications. https://doi.org/10.1109/TCOMM.2025.3621060

  11. Alauthman, M., Aslam, N., Al-Qerem, A., Aldweesh, A., Sureephong, P. (2026). Generative Adversarial Networks for Intrusion Detection Systems: A Comprehensive Survey of Applications, Challenges, and Research Directions. Arabian Journal for Science and Engineering. https://doi.org/10.1007/s13369-026-11103-6

  12. Athama, A., Wang, K., Chen, X., Li, Y. (2024). Semantic Communications for Healthcare Applications: Opportunities and Challenges. 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT). https://doi.org/10.1109/BDCAT63179.2024.00066

  13. Wan, F., Fondrevelle, J., Wang, T., Wang, K., Duclos, A. (2024). Optimizing Small-Scale Surgery Scheduling with Large Language Model. Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics. https://doi.org/10.5220/0012894400003822

  14. Zhu, R., Yang, M., Wang, Q. (2024). ShuffleFL: Addressing Heterogeneity in Multi-Device Federated Learning. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8(2), Article 85, 34 pages. https://doi.org/10.1145/3659621

  15. Liu, J., Chang, Z., Ye, C., Mumtaz, S., Hämäläinen, T. (2024). Game-Theoretic Power Allocation and Client Selection for Privacy-Preserving Federated Learning in IoMT. IEEE Transactions on Communications. https://doi.org/10.1109/TCOMM.2024.3523968

  16. Yang, M., Zhu, R., Wang, Q., Yang, J. (2024). FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning. ICLR. https://openreview.net/forum?id=8IsP38Hpq2