Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2025

Overview

Overview

The Stochastic Numerics and Statistical Learning Workshop 2025 returns to KAUST after three highly successful editions, continuing to bring together researchers, faculty and students exploring stochastic algorithms, statistical learning, optimization, and approximation. The workshop will feature contributions that establish mathematical foundations for algorithmic analysis and highlight applications across various domains.

This scientific meeting will focus on stochastic algorithms and their rigorous numerical analysis in solving complex problems. These algorithms play a crucial role in tackling computational challenges across multiple fields, including machine learning, stochastic optimal control, quantitative finance, data assimilation, and Bayesian statistics. Their applications span a wide range of disciplines, making them highly relevant to ongoing research at KAUST and within the Kingdom.

Invited Speakers

External speakers for the event include:

• Markus Bachmayr, RWTH Aachen
• Peter Friz, Technical University of Berlin
• Mike Giles, University of Oxford
• Christoph Reisinger, University of Oxford
• Ajay Jasra, The Chinese University of Hong Kong, Shenzhen
• Ahmed Kebaier, Université d'Évry
• Fabio Nobile, École Polytechnique Fédérale de Lausanne (EPFL)
• Sebastian Reich, Potsdam University
• Robert Scheichl, Heidelberg University
• Anders Szepessy, KTH Stockholm 

Poster Session

As part of the workshop, two poster sessions will take place on May 18 and 19. Participants interested in presenting a poster must submit a title and abstract through the registration from.

ePoster Submission and Registration Form

Key Dates and Deadlines

• March 1 – Registration and poster submission opens
• April 7 – Submission deadline
• April 14 – Accepted authors receive poster upload instructions
• May 10 – Final deadline for poster upload