Federated learning

KAUST advances scalable AI through global collaboration

1 min read · Wed, Nov 12 2025

machine learning LLM Federated learning Distributed algorithms

KAUST brings global experts together to advance scalable AI and tackle the challenges of training large models.

Rafal Szlendak

Ph.D. Student, Applied Mathematics and Computational Science

optimization Federated learning

Rafał Szlendak is an MS/PhD student in the AMCS program under the supervision of Prof. Peter Richtarik. His biggest passions are research, weightlifting and travelling. His career path is motivated by his endless passion for self-development and discovery. Education and Early Career Rafał Szlendak has obtained his Bachelor's degree in Mathematics and Statistics from University of Warwick Research Interest In his research Rafał focuses on stochastic gradient descent algorithms for large-scale machine learning problems. His primary goal is developing state-of-the-art methods with sound

Laurent Condat

Senior Research Scientist, Computer Science

optimization Federated learning Distributed algorithms Signal and Image Processing

I am a senior researcher working in optimization, in the group of Prof. Peter Richtárik.

Grigorii Malinovskii

Ph.D. Student, Computer Science

machine learning convex optimization Federated learning

I am a PhD student in Applied Mathematics and Computational Science at King Abdullah University of Science and Technology, advised by Prof. Peter Richtárik, working on optimization theory and its applications in Machine Learning. My hobbies include drums, fitness, martial arts, football, and basketball.