About

I’m Osama Abu Hamdan, a Computer Science Ph.D. candidate focused on federated learning, distributed systems, and networked AI. My work centers on improving communication efficiency, scalability, and real-world deployment of collaborative machine learning systems, aiming to bridge cutting-edge research with practical, deployable solutions.

My academic work includes designing frameworks like FLEET, a scalable FL testbed, and SmartFLow, an SDN-based communication layer that speeds up cross-silo training. I’ve published my research in leading venues such as IEEE CCNC, IEEE EDGE, IEEE CSR, and IEEE LANMAN, contributing to advances in distributed AI performance and reliability.

Alongside research, I bring solid industry experience in backend development, cloud/edge systems, and software-defined networking. I’ve built large-scale platforms at Atypon (John Wiley & Sons), led engineering for apps like Wird, and delivered high-performance systems using Django, Spring, and PostgreSQL.

View my full CV here.