I am a Senior Lecturer and telecommunications-AI researcher specializing in intelligent and distributed network systems.
My work combines federated learning, explainable AI, and intelligent 5G/6G network research. It builds on
extensive industry experience in microwave backhaul, transport planning, and network optimization. I have published
AI-driven methods for backhaul optimization, KPI monitoring, federated learning, and THz communications. I developed
FedPA, a performance-aware framework for selective and resource-efficient federated aggregation. My current research
explores Explainable and Agentic AI for telecom planning and autonomous operations. This direction
integrates intelligent reasoning with engineering models, simulators, and network optimization tools. My goal is to
develop trustworthy telecom AI that respects engineering constraints and human oversight. I also have experience
in grant writing, project delivery, technical reporting, and research supervision. My research has contributed to 25
indexed publications covering telecom networks, healthcare AI, and distributed intelligence.