1. Maintaining flexibility in smart grid consumption through deep learning and deepreinforcement learning

Gallego, F., Martín, C., Díaz, M., & Garrido, D. (2023). Maintaining flexibility in smart grid consumption through deep learning and reinforcement learning. Energy and AI, 13, 100241.

4. Designing Future Wireless Networks (FWN)s With Net Zero (NZ) and Zero Touch (ZT) Perspective

Abbas, W.B., Ahmed, Q.Z., Khan, F.A., Mian, N.S., Lazaridis, P.I., Sureephong, P. (2023). Designing Future Wireless Networks (FWN)s With Net Zero (NZ) and Zero Touch (ZT) Perspective. IEEE Access, 11, (pp. 83301-83321). IEEE.

5. Enabling Uncoordinated Dynamic Spectrum Sharing Between LTE and NR Networks

Girmay, M., Maglogiannis, V., Naudts, D., Waele, T.D., Poorter, E.D., Shadid, A., Vincent Poor, H., Moerman, I. (2023). Enabling Uncoordinated Dynamic Spectrum Sharing Between LTE and NR Networks. IEEE Transactions on Wireless Communications. IEEE

6. Hardware-accelerated Real-time Drift-awareness for Robust Deep Learning on Wireless RF Data

Ganewattha, C., Khan, Z., Lehtomäki, J., Latva-Aho, M. (2023). Hardware-accelerated Real-time Drift-awareness for Robust Deep Learning on Wireless RF Data. ACM Trans. Reconfigurable Technol. Syst., 16, 2, Article 19. Association for Computing Machinery

7. Heuristic Antenna Selection and Precoding for a Massive MIMO System

Abbas, W. B., Khalid, S., Ahmed, Q. Z., Khalid, F., Alade, T.T., Sureephong, P. (2023). Heuristic Antenna Selection and Precoding for a Massive MIMO System. IEEE Open Journal of the Communications Society, vol. 5, (pp. 83-96). IEEE.

8. Local Energy Market Design for Power- and Hydrogen-Based Microgrids Considering a Hybrid Uncertainty Controlling Approach

Saatloo, A. M., Mehrabi, A., Marzband, M., Mirzaei, M.A., Aslam, N. (2023). Local Energy Market Design for Power- and Hydrogen-Based Microgrids Considering a Hybrid Uncertainty Controlling Approach. IEEE Transactions on Sustainable Energy, vol. 15, no. 1, (pp. 398-413).

9. Novel Fine-Tuned Attribute Weighted Naïve Bayes NLoS Classifier for UWB Positioning

Che, F., Ahmed, Q. Z., Khan, F. A. and Khan, F. A.(2023). Novel Fine-Tuned Attribute Weighted Naïve Bayes NLoS Classifier for UWB Positioning. IEEE Communications Letters, vol. 27, no. 4, (pp. 1130-1134). IEEE.

10. Spectrum Options and Allocations for 6G: A Regulatory and Standardization Review

Alsaedi, W. K., Ahmadi, H., Khan, Z.,Grace, D., (2023). Spectrum Options and Allocations for 6G: A Regulatory and Standardization Review. IEEE Open Journal of the Communications Society, vol. 4, (pp. 1787-1812). IEEE.

11. Evaluation of Prophet for Wireless Time Series Forecasting

Zu, M.M., Sone, S.P., Lehtomäki, J., Khan, Z., (2023). Evaluation of Prophet for Wireless Time Series Forecasting. 31st Telecommunications Forum (TELFOR), Belgrade, Serbia, 2023, (pp. 1-4). IEEE

12. Safety Analysis of Automatic Train Operation Based on ETCS

Tang, Z., Zhao, N., Khan, K., Wolter, K. (2023). Safety Analysis of Automatic Train Operation Based on ETCS. In: Milius, B., Collart-Dutilleul, S., Lecomte, T. (eds) Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification. RSSRail 2023. Lecture Notes in Computer Science, vol 14198. Springer, Cham.

13. Online Learning and Continuous Model Upgrading with Data Streams Through the Kafka-Ml Framework.

Carnero, A., Martín, C., Jeon, G., & Díaz, M. Online Learning and Continuous Model Upgrading with Data Streams Through the Kafka-Ml Framework. Available at SSRN 4681565.

2. The orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka‐ML: A deep‐learning performance comparative

Chaves, A. J., Martín, C., & Díaz, M. (2023). The orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka‐ML: A deep‐learning performance comparative. Expert Systems, e13287.

3. Intelligent Spectrum Sharing Between LTE and Wi-Fi Networks using Muted MBSFN Subframes

Girmay, M., Avila-Campos, P., Maglogiannis, V., Naudts, D., Shahid, A., & Moerman, I. (2023, April). Intelligent Spectrum Sharing Between LTE and Wi-Fi Networks using Muted MBSFN Subframes. In 2023 IEEE Wireless and Microwave Technology Conference (WAMICON) (pp. 13-16). IEEE.