Skip to content
GCC AI Research

Why the World Cup is a random process with a drift

KAUST ·

Summary

KAUST Professor Peter Markowich discusses the role of mathematics in football, describing a match as a random process with a drift. The randomness stems from player conditions, referee decisions, weather, and more, while the drift represents the higher probability of the better team winning. He notes that the complexity arising from 11 players on each side increases the randomness compared to sports like tennis. Why it matters: This perspective highlights the interplay of chance and skill in sports, offering a mathematical lens for understanding game dynamics.

Get the weekly digest

Top AI stories from the GCC region, every week.

Related

Learn to control

MBZUAI ·

Patrick van der Smagt, Director of AI Research at Volkswagen Group, discussed the use of generative machine learning models for predicting and controlling complex stochastic systems in robotics. The talk highlighted examples in robotics and beyond and addressed the challenges of achieving quality and trust in AI systems. He also mentioned his involvement in a European industry initiative on trust in AI and his membership in the AI Council of the State of Bavaria. Why it matters: Understanding control in robotics, along with trust in AI, are key issues for further development of autonomous systems, especially in industrial applications within the GCC region.

SGD from the Lens of Markov process: An Algorithmic Stability Perspective

MBZUAI ·

A Marie Curie Fellow from Inria and UIUC presented research on stochastic gradient descent (SGD) through the lens of Markov processes, exploring the relationships between heavy-tailed distributions, generalization error, and algorithmic stability. The research challenges existing theories about the monotonic relationship between heavy tails and generalization error. It introduces a unified approach for proving Wasserstein stability bounds in stochastic optimization, applicable to convex and non-convex losses. Why it matters: The work provides novel insights into the theoretical underpinnings of stochastic optimization, relevant to researchers at MBZUAI and other institutions in the region working on machine learning algorithms.

The role of data-driven models in quantifying uncertainty

KAUST ·

KAUST Professor Raul Tempone, an expert in Uncertainty Quantification (UQ), has been appointed as an Alexander von Humboldt Professor at RWTH Aachen University in Germany. This professorship will enable him to further his research on mathematics for uncertainty quantification with new collaborators. Tempone believes the KAUST Strategic Initiative for Uncertainty Quantification (SRI-UQ) contributed to this award. Why it matters: This appointment enhances KAUST's visibility and facilitates cross-fertilization between European and KAUST research groups, benefiting both institutions and attracting talent.

KAUST becomes first FIFA research institute in the Middle East and Asia

KAUST ·

KAUST has been selected as the first FIFA Research Institute in the Middle East and Asia. KAUST will apply its research expertise to advance football-related studies, initially focusing on developing datasets that enable deeper insights into the game. The collaboration’s first project focuses on developing AI algorithms to analyze historical FIFA World Cup broadcast footage, while the second project leverages player and ball tracking data from the FIFA World Cup 2022™ Qatar and the FIFA Women’s World Cup 2023™ Australia & New Zealand. Why it matters: This partnership strengthens the intersection of sport, academia, and industry in the region through high-impact scientific inquiry.