| A programmable ROADM system for SDM/WDM networks R Yang, L Liu, S Yan, D Simeonidou Applied Sciences 11 (9), 4195, 2021 | 7 | 2021 |
| DRL-based energy-efficient baseband function deployments for service-oriented Open RAN H Li, A Emami, KDR Assis, A Vefeas, R Yang, R Nejabati, S Yan, ... IEEE Transactions on Green Communications and Networking, 2023 | 3 | 2023 |
| 986 km field trial of cascaded ANN-based link-penalty models for QoT prediction R Yang, S Shen, H Li, Z Shi, R Wang, R Nejabati, S Yan, D Simeonidou 2023 Optical Fiber Communications Conference and Exhibition (OFC), 1-3, 2023 | 3 | 2023 |
| LSTM Assisted Optical Transmission Performance Analysis over a 493-km Field-Trial S Shen, R Yang, H Li, Z Shi, R Wang, R Nejabati, S Yan, D Simeonidou Optical Fiber Communication Conference, W4G. 4, 2023 | 3 | 2023 |
| Field-trial demonstration of ML deployment in optical networks using telemetry and AI engine S Shen, R Yang, H Li, Y Teng, R Wang, R Nejabati, S Yan, D Simeonidou 49th European Conference on Optical Communications (ECOC 2023) 2023, 1126-1129, 2023 | 1 | 2023 |
| DRL-based RMSCA for SDM Networks with Core Switching in Multi-Core Fibres Y Teng, R Yang, C Natalino, S Shen, P Monti, R Nejabati, S Yan, ... 2023 International Conference on Photonics in Switching and Computing (PSC), 1-3, 2023 | 1 | 2023 |
| Deep-reinforcement-learning-based RMSCA for space division multiplexing networks with multi-core fibers [Invited Tutorial] Y Teng, C Natalino, H Li, R Yang, J Majeed, S Shen, P Monti, R Nejabati, ... Journal of Optical Communications and Networking 16 (7), C76-C87, 2024 | | 2024 |
| A Machine Learning-Assisted Quantum and Classical Co-existence System R Yang, R Wang, A Seferidis, T Omigbodun, S Bahrani, RD Oliveira, ... Optical Fiber Communication Conference, M2J. 2, 2024 | | 2024 |
| Energy-Efficient Baseband Function Deployments for Service-Oriented Open RAN. H Li, A Emami, KDR Assis, A Vafeas, R Yang, R Nejabati, S Yan, ... CoRR, 2022 | | 2022 |
| Convergence Analysis and Latency Minimization for Semi-Federated Learning in Massive IoT Networks...................... H Li, A Emami, KDR Assis, A Vafeas, R Yang, R Nejabati, S Yan, ... | | |
