A Cloud Native SLA-Driven Stochastic Federated Learning Policy for 6G Zero-Touch Network Slicing. - Swastika Roy; Hatim Chergui; Luis Sanabria-Russo; Christos V. Verikoukis (ICC, 2022)

Joint Explainability and Sensitivity-Aware Federated Deep Learning for Transparent 6G RAN Slicing. - Swastika Roy; Farhad Rezazadeh; Hatim Chergui; Christos V. Verikoukis (ICC, 2023)

Towards Bridging the FL Performance-Explainability Trade-Off: A Trustworthy 6G RAN Slicing Use-Case. - Swastika Roy; Hatim Chergui; Christos V. Verikoukis (CoRR, 2023)

Intent-Driven Deployment and Live Migration Using LLM. - João Pedro Fonseca 001; Gereziher Adhane; Konstantinos Togias; Jhofre Ojeda; Swastika Roy; Golshan Famitafreshi; Kostas Ramantas; John S. Vardakas; Christos V. Verikoukis (CAMAD, 2024)

Realizing Intent-Driven Network Management with TM Forum Standards. - João Pedro Fonseca 001; Gereziher Adhane; Konstantinos Togias; Jhofre Ojeda; Swastika Roy; Golshan Famitafreshi; Kostas Ramantas; John S. Vardakas; Christos V. Verikoukis (CAMAD, 2024)

Real-Time Machine Learning-Based IoT Data Analysis in the Edge Cloud Continuum Using AC3. - Jhofre Ojeda; Dimitrios Amaxilatis; Nikolaos Tsironis; Themistoklis Sarantakos; João Fonseca; Gereziher Adhane; Golshan Famitafreshi; Swastika Roy; Shreya K. Chari; Navideh Ghafouri; Kostas Ramantas; Christos V. Verikoukis (CAMAD, 2024)

Federated Machine Reasoning for Resource Provisioning in 6G O-RAN. - Swastika Roy; Hatim Chergui; Adlen Ksentini; Christos V. Verikoukis (CoRR, 2024)

Toward Bridging the FL Performance-Explainability Tradeoff: A Trustworthy 6G RAN Slicing Use-Case. - Swastika Roy; Hatim Chergui; Christos V. Verikoukis (IEEE Trans. Veh. Technol., 2024)

Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing. - Swastika Roy; Hatim Chergui; Christos V. Verikoukis (IEEE Trans. Cogn. Commun. Netw., 2024)

XAI-Driven Client Selection for Federated Learning in Scalable 6G Network Slicing. - Martino Chiarani; Swastika Roy; Christos V. Verikoukis; Fabrizio Granelli (CoRR, 2025)

6G-INTENSE: Intent-Driven Native Artificial Intelligence Architecture Supporting Network-Compute Abstraction and Sensing at the Deep Edge. - Akram Boutouchent; Abdelkader Mekrache; Adlen Ksentini; Gereziher Adhane; João Pedro Celestino da Fonseca; Joseph McNamara; Kostas Ramantas; Marco Palena; Marius Iordache; Renato Lo Cigno; Salwa Mostafa; Swastika Roy; et al. (IEEE Veh. Technol. Mag., 2025)