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; 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, Germany
  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
• Malik, Gulmina; Masood, Muhammad Umar; Ali, Ahtisham; Cheruvakkadu Mohamed, Mashboob; ... (2026)
  Machine Learning–Based Detection and Classification of Overlapping Fiber Anomalies. In: IEEE PHOTONICS TECHNOLOGY LETTERS, vol. 38, pp. 1157-1160. ISSN 1041-1135
  Contributo su Rivista
• Mohamed, Mashboob Cheruvakkadu; Ambrosone, Renato; D'Ingillo, Rocco; Masood, Muhammad ... (2025)
  Leveraging Digital Twins to Build Comprehensive Network Failure Databases for Predictive Machine Learning in Optical Transport Networks. In: 2025 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Delhi (Ind), 15-18 Dicembre 2025, pp. 1-6. ISBN: 979-8-3315-2682-5
  Contributo in Atti di Convegno (Proceeding)