Towards a NetFlow Implementation for OpenFlow Software-Defined Networks. - José Suárez-Varela; Pere Barlet-Ros (ITC, 2017)

Reinventing NetFlow for OpenFlow Software-Defined Networks. - José Suárez-Varela; Pere Barlet-Ros (CoRR, 2017)

Towards accurate classification of HTTPS traffic in Software-Defined Networks. - José Suárez-Varela; Pere Barlet-Ros (I2MTC, 2018)

SBAR: SDN flow-Based monitoring and Application Recognition. - José Suárez-Varela; Pere Barlet-Ros (SOSR, 2018)

Flow monitoring in Software-Defined Networks: Finding the accuracy/performance tradeoffs. - José Suárez-Varela; Pere Barlet-Ros (Comput. Networks, 2018)

Towards more realistic network models based on Graph Neural Networks. - Arnau Badia-Sampera; José Suárez-Varela; Paul Almasan; Krzysztof Rusek; Pere Barlet-Ros; Albert Cabellos-Aparicio (CoNEXT Companion, 2019)

Feature Engineering for Deep Reinforcement Learning Based Routing. - José Suárez-Varela; Albert Mestres; Junlin Yu; Li Kuang; Haoyu Feng; Pere Barlet-Ros; Albert Cabellos-Aparicio (ICC, 2019)

Detecting cryptocurrency miners with NetFlow/IPFIX network measurements. - Jordi Zayuelas i Muñoz; José Suárez-Varela; Pere Barlet-Ros (M&N, 2019)

Routing Based on Deep Reinforcement Learning in Optical Transport Networks. - José Suárez-Varela; Albert Mestres; Junlin Yu; Li Kuang; Haoyu Feng; Pere Barlet-Ros; Albert Cabellos-Aparicio (OFC, 2019)

Challenging the generalization capabilities of Graph Neural Networks for network modeling. - José Suárez-Varela; Sergi Carol-Bosch; Krzysztof Rusek; Paul Almasan; Marta Arias; Pere Barlet-Ros; Albert Cabellos-Aparicio (SIGCOMM Posters and Demos, 2019)

Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN. - Krzysztof Rusek; José Suárez-Varela; Albert Mestres; Pere Barlet-Ros; Albert Cabellos-Aparicio (SOSR, 2019)

Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case. - Paul Almasan; José Suárez-Varela; Arnau Badia-Sampera; Krzysztof Rusek; Pere Barlet-Ros; Albert Cabellos-Aparicio (CoRR, 2019)

Routing in optical transport networks with deep reinforcement learning. - José Suárez-Varela; Albert Mestres; Junlin Yu; Li Kuang; Haoyu Feng; Albert Cabellos-Aparicio; Pere Barlet-Ros (JOCN, 2019)

Applying Graph-based Deep Learning To Realistic Network Scenarios. - Miquel Ferriol Galmés; José Suárez-Varela; Pere Barlet-Ros; Albert Cabellos-Aparicio (CoRR, 2020)

RouteNet: Leveraging Graph Neural Networks for Network Modeling and Optimization in SDN. - Krzysztof Rusek; José Suárez-Varela; Paul Almasan; Pere Barlet-Ros; Albert Cabellos-Aparicio (IEEE J. Sel. Areas Commun., 2020)

Enabling knowledge-defined networks : deep reinforcement learning, graph neural networks and network analytics. - José Rafael Suárez-Varela Macià (2020)

Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges. - Paul Almasan; José Suárez-Varela; Bo Wu; Shihan Xiao; Pere Barlet-Ros; Albert Cabellos-Aparicio (HPSR, 2021)

Is Machine Learning Ready for Traffic Engineering Optimization? - Guillermo Bernárdez; José Suárez-Varela; Albert López; Bo Wu; Shihan Xiao; Xiangle Cheng; Pere Barlet-Ros; Albert Cabellos-Aparicio (ICNP, 2021)

IGNNITION: fast prototyping of graph neural networks for communication networks. - David Pujol-Perich; José Suárez-Varela; Miquel Ferriol Galmés; Bo Wu; Shihan Xiao; Xiangle Cheng; Albert Cabellos-Aparicio; Pere Barlet-Ros (SIGCOMM Posters and Demos, 2021)

The graph neural networking challenge: a worldwide competition for education in AI/ML for networks. - José Suárez-Varela; Miquel Ferriol Galmés; Albert López; Paul Almasan; Guillermo Bernárdez; David Pujol-Perich; Krzysztof Rusek; Loïck Bonniot; Christoph Neumann 001; François Schnitzler; François Taïani; Martin Happ; et al. (Comput. Commun. Rev., 2021)

Scaling Graph-based Deep Learning models to larger networks. - Miquel Ferriol Galmés; José Suárez-Varela; Krzysztof Rusek; Pere Barlet-Ros; Albert Cabellos-Aparicio (CoRR, 2021)

IGNNITION: Bridging the Gap between Graph Neural Networks and Networking Systems. - David Pujol-Perich; José Suárez-Varela; Miquel Ferriol; Shihan Xiao; Bo Wu; Albert Cabellos-Aparicio; Pere Barlet-Ros (IEEE Netw., 2021)

Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing. - Krzysztof Rusek; Paul Almasan; José Suárez-Varela; Piotr Cholda; Pere Barlet-Ros; Albert Cabellos-Aparicio (CNSM, 2022)

RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation. - Miquel Ferriol Galmés; Krzysztof Rusek; José Suárez-Varela; Shihan Xiao; Xiang Shi; Xiangle Cheng; Bo Wu; Pere Barlet-Ros; Albert Cabellos-Aparicio (INFOCOM, 2022)

Exploring the Limitations of Current Graph Neural Networks for Network Modeling. - Martin Happ; Jia Lei Du; Matthias Herlich; Christian Maier; Peter Dorfinger; José Suárez-Varela (NOMS, 2022)

Network Digital Twin: Context, Enabling Technologies, and Opportunities. - Paul Almasan; Miquel Ferriol Galmés; Jordi Paillisse; José Suárez-Varela; Diego Perino; Diego R. López; Antonio Agustin Pastor Perales; Paul Harvey 002; Laurent Ciavaglia; Leon Wong; Vishnu Ram; Shihan Xiao; et al. (IEEE Commun. Mag., 2022)

Building a Digital Twin for network optimization using Graph Neural Networks. - Miquel Ferriol Galmés; José Suárez-Varela; Jordi Paillisse; Xiang Shi; Shihan Xiao; Xiangle Cheng; Pere Barlet-Ros; Albert Cabellos-Aparicio (Comput. Networks, 2022)

Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case. - Paul Almasan; José Suárez-Varela; Krzysztof Rusek; Pere Barlet-Ros; Albert Cabellos-Aparicio (Comput. Commun., 2022)

Digital Twin Network: Opportunities and Challenges. - Paul Almasan; Miquel Ferriol Galmés; Jordi Paillisse; José Suárez-Varela; Diego Perino; Diego R. López; Antonio Agustin Pastor Perales; Paul Harvey 002; Laurent Ciavaglia; Leon Wong; Vishnu Ram; Shihan Xiao; et al. (CoRR, 2022)

RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation. - Miquel Ferriol Galmés; Krzysztof Rusek; José Suárez-Varela; Shihan Xiao; Xiangle Cheng; Pere Barlet-Ros; Albert Cabellos-Aparicio (CoRR, 2022)

Unveiling the potential of Graph Neural Networks for robust Intrusion Detection. - David Pujol-Perich; José Suárez-Varela; Albert Cabellos-Aparicio; Pere Barlet-Ros (SIGMETRICS Perform. Evaluation Rev., 2022)

Enhancing 5G Radio Planning with Graph Representations and Deep Learning. - Paul Almasan; José Suárez-Varela; Andra Lutu; Albert Cabellos-Aparicio; Pere Barlet-Ros (5G-MeMZ@SIGCOMM, 2023)

Detecting Contextual Network Anomalies with Graph Neural Networks. - Hamid Latif; José Suárez-Varela; Albert Cabellos-Aparicio; Pere Barlet-Ros (GNNet@CoNEXT, 2023)

Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities. - José Suárez-Varela; Paul Almasan; Miquel Ferriol Galmés; Krzysztof Rusek; Fabien Geyer; Xiangle Cheng; Xiang Shi; Shihan Xiao; Franco Scarselli; Albert Cabellos-Aparicio; Pere Barlet-Ros (IEEE Netw., 2023)

MAGNNETO: A Graph Neural Network-Based Multi-Agent System for Traffic Engineering. - Guillermo Bernárdez; José Suárez-Varela; Albert López; Xiang Shi; Shihan Xiao; Xiangle Cheng; Pere Barlet-Ros; Albert Cabellos-Aparicio (IEEE Trans. Cogn. Commun. Netw., 2023)

RouteNet-Fermi: Network Modeling With Graph Neural Networks. - Miquel Ferriol Galmés; Jordi Paillisse; José Suárez-Varela; Krzysztof Rusek; Shihan Xiao; Xiang Shi; Xiangle Cheng; Pere Barlet-Ros; Albert Cabellos-Aparicio (IEEE/ACM Trans. Netw., 2023)

Through the Telco Lens: A Countrywide Empirical Study of Cellular Handovers. - Michail Kalntis; José Suárez-Varela; Jesús Omana Iglesias; Anup Kiran Bhattacharjee; George Iosifidis; Fernando A. Kuipers; Andra Lutu (IMC, 2024)

An Evaluation of RAN Sustainability Strategies in Production Networks. - Orlando E. Martínez-Durive; José Suárez-Varela; Jesús Omana Iglesias; Andra Lutu; Marco Fiore 001 (INFOCOM, 2025)

TSGFM - Towards a Graph Foundation Model for Time Series Analysis in Network Monitoring. - Hamid Latif-Martínez; Pedro Casas; José Suárez-Varela; Albert Cabellos-Aparicio; Pere Barlet-Ros (TMA, 2025)

GAT-AD: Graph Attention Networks for contextual anomaly detection in network monitoring. - Hamid Latif-Martínez; José Suárez-Varela; Albert Cabellos-Aparicio; Pere Barlet-Ros (Comput. Ind. Eng., 2025)

GraphCC: A practical graph learning-based approach to Congestion Control in datacenters. - Guillermo Bernárdez; José Suárez-Varela; Xiang Shi; Shihan Xiao; Xiangle Cheng; Pere Barlet-Ros; Albert Cabellos-Aparicio (Comput. Networks, 2025)

Uncovering Issues in the Radio Access Network by Looking at the Neighbors. - José Suárez-Varela; Andra Lutu (CoRR, 2025)