Mashboob Cheruvakkadu Mohamed

Argomento di ricerca

Optical Communication Networks, Machine Learning/AI for Optical Networks, Optical Network Tomography

Tutori

• Vittorio Curri
• Emanuele Virgillito

• Malik, Gulmina; Masood, Muhammad Umar; Ali, Ahtisham; Cheruvakkadu Mohamed, Mashboob; ... (In stampa)
  A Hybrid XGBoost–CNN Framework for Robust SOP Anomaly Detection in Optical Networks. In: 26th International Conference on Transparent Optical Networks ICTON 2026, Prague (Cze), 12-16 July 2026
  Contributo in Atti di Convegno (Proceeding)
• Malik, Gulmina; Masood, Muhammad Umar; Ali, Ahtisham; Cheruvakkadu Mohamed, Mashboob; ... (In stampa)
  Multi-Threat Detection in Optical Networks Using Deep Neural Networks. In: IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN), Abu Dhabi (UAE), 8 - 11 June 2026
  Contributo in Atti di Convegno (Proceeding)
• Malik, Gulmina; Masood, Muhammad Umar; Ambrosone, Renato; Ali, Ahtisham; Cheruvakkadu ... (2026)
  Real-Time Vibration Anomaly Detection in Operational Metropolitan Optical Networks Using Machine Learning. In: 30th International Conference on Optical Network Design and Modelling (ONDM), Munich (Ger), 12-15 May 2026. ISBN: 978-3-903176-78-2
  Contributo in Atti di Convegno (Proceeding)
• Mohamed, Mashboob Cheruvakkadu; D'Ingillo, Rocco; Ambrosone, Renato; Masood, Muhammad ... (2026)
  Experimentally Characterized Digital Twin for Machine Learning Based EDFA Failure Prognostics. In: Optical Fiber Communication Conference, 2026, Los Angeles (USA), 15-19 March 2026
  Contributo in Atti di Convegno (Proceeding)
• Mohamed, Mashboob Cheruvakkadu; Ambrosone, Renato; Masood, Muhammad Umar; Malik, ... (2026)
  Reinforcement Learning to Enhance Digital Twin Based EDFA Fault Prediction in Optical Networks. In: IEEE PHOTONICS TECHNOLOGY LETTERS, vol. 38, pp. 1227-1230. ISSN 1041-1135
  Contributo su Rivista