KAUST Ph.D. student Mohammed Aljahdali received the Best Paper award at the International Conference on Federated Learning Technologies and Applications (FLTA) 2025 for his research on federated learning. His paper, "Flashback: Understanding and Mitigating Forgetting in Federated Learning," introduces an algorithm to help AI systems retain knowledge across diverse datasets while preserving privacy. Aljahdali's research, supervised by Professor Marco Canini, focuses on training machine learning models directly on user devices. Why it matters: This award recognizes the growing talent and impactful research emerging from Saudi universities in the field of privacy-preserving AI.
KAUST is hosting a workshop on distributed training in November 2025, led by Professors Peter Richtarik and Marco Canini, focusing on scaling large models like LLMs and ViTs. Richtarik's team recently solved a 75-year-old problem in asynchronous optimization, developing time-optimal stochastic gradient descent algorithms. This research improves the speed and reliability of large model training and supports applications in distributed and federated learning. Why it matters: KAUST's focus on scalable AI and federated learning contributes to Saudi Arabia's Vision 2030 goals and addresses critical challenges in AI deployment and data privacy.
KAUST faculty member Marco Canini is researching networked systems, focusing on improving their design, implementation, and operation. His work centers on Software-Defined Advanced Networked and Distributed Systems (SANDS). Canini aims to address challenges related to reliability, performance, security, and energy efficiency in large-scale networked computer systems. Why it matters: This research contributes to the development of more dependable and efficient digital infrastructure in Saudi Arabia, aligning with KAUST's mission to advance science and technology.
Marco Canini is an assistant professor of computer science at KAUST in the Computer, Electrical and Mathematical Science and Engineering Division. He is highlighted in a faculty focus piece by KAUST Discovery. Why it matters: Showcases talent at KAUST.