software development

Extreme Computing Universals

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B9 L2 R2325

This talk redefines "extreme" computing as operating under severe resource constraints rather than just massive scale, outlining universal algorithmic, hardware, and system-level strategies to overcome these challenges, illustrated by KAUST success stories.

Error Feedback for Communication-Efficient First and Second-Order Distributed Optimization: Theory and Practical Implementation

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B9 L2 R2325

This seminar will discuss advancements in Federated Learning, including theoretical improvements to the Error Feedback method (EF21) for communication-efficient distributed training and the development of significantly more practical and efficient implementations of the Federated Newton Learn (FedNL) algorithm.
Qusai Ghabrah

Qusai A. Ghabrah

M.S. Student, Computer Science
Qusai Ghabrah is a computer science master's student at KAUST with a strong background in software engineering and technical project management, who has worked on an LLM-assisted system testing tool for microservices as part of his research project.

Konstantin Burlachenko

Ph.D. Student, Computer Science
Konstantin's research focuses on large-scale mathematical optimization systems for machine learning and artificial intelligence, especially those requiring high-performance computing approaches.

David Keyes

David Keyes works at the interface of computational science and engineering and high performance computing, which he helped edit into the DNA of KAUST as a founding Dean in 2009 and then as director of the Extreme Computing Research Center. He currently serves as Senior Associate to the President, Chair of the KAUST RDIA Economies of the Future committee, and delegate to the Saudi Center for the Fourth Industrial Revolution.