معرفی
Marco Canini is Professor of Computer Science at KAUST's Computer, Electrical and Mathematical Sciences & Engineering division. His research creates next-generation computing infrastructure for distributed AI/ML systems, focusing on network programmability and efficient large-scale computation.
Research interests span distributed systems, cloud computing, and programmable networks, with current focus on systems support for distributed machine learning. His work develops practical implementations deployable in real-world environments.
Recent publications demonstrate strong trends in optimizing distributed training through hardware acceleration (SmartNICs), communication efficiency (quantization methods), and privacy-preserving techniques (federated/split learning).
