SIAM Conference on Uncertainty Quantification (UQ24)

SIAM Conference

SIAM Conference on Uncertainty Quantification (UQ24)

February 27 - March 1, 2024

Savoia Excelsior Palace Trieste and Stazione Marittima | Trieste, Italy

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Conference Announcements

Announcements and important information for this conference.


Attendees of UQ24 might be interested in attending the satellite event: Power of Diversity in Uncertainty (POD-UQ)

A searchable abstract document is available here!



Upcoming conference deadlines and important dates.

About the Conference

About the Conference


This is the conference of the SIAM Activity Group on Uncertainty Quantification.
This conference is being held in cooperation with the American Statistical Association (ASA) and GAMM Activity Group on Uncertainty Quantification (GAMM AG UQ).

Uncertainty quantification (UQ) is essential for establishing the reliability of predictions made by computational models. Such models are often deterministic, and the UQ discipline has traditionally focused on how to quantify uncertainty in that case. Statistical methods play a major role in that effort, and represent an alternative modeling strategy when less is known about the system of interest. The two approaches are naturally synergistic, and with the emergence of machine learning as a practical tool, it is becoming more important than ever to view the whole UQ ecosystem through a unifying lens.

UQ is application-driven and inherently interdisciplinary, relying on a broad range of mathematical and statistical foundations, domain knowledge, and algorithmic and computational tools. UQ24 will bring together mathematicians, statisticians, scientists, engineers, and others interested in the theory, development, and application of UQ methods. Major conference themes will include mathematical and statistical foundations, data-driven approaches and computational advances, applications of UQ in biology, medicine, environmental and climate sciences, decision making for societal benefit, and all areas of physical science and engineering. The goal of the conference is to provide a forum for exchanging ideas between diverse groups from academia, industry, and government laboratories, thereby enhancing communication and contributing to future advances in the field.

Included Themes

Included Themes

Major Themes

  • Computational advances 
  • Data-driven methods 
  • Machine learning for UQ and UQ for machine learning 
  • Mathematical and statistical foundations of UQ 
  • UQ for decision making and societal benefit 
  • UQ in biosciences, bioengineering, and biomedicine 
  • UQ in climate and environmental sciences 
  • UQ in engineering 
  • UQ in physical sciences


  • Adversarial approaches to UQ 
  • Combining physical and statistical modeling 
  • Computer experiments and spatial statistical methods 
  • Data assimilation and data fusion 
  • Design of experiments 
  • Gaussian process modeling and prediction 
  • High-dimensional approximation and dimension reduction 
  • Infinite-dimensional analysis and approximation 
  • Inverse problems 
  • Model discrepancy 
  • Multiscale, multilevel, and multifidelity UQ methods 
  • Optimization 
  • Physics-informed machine learning 
  • Rare and extreme events 
  • Reduced-order models 
  • Remote sensing 
  • Risk analysis based on UQ 
  • Surrogate models and emulators 
  • UQ for complex and coupled systems 
  • UQ for digital twins 
  • UQ for spatial and spatio-temporal processes 
  • UQ-informed policy and decisions 
  • Verification and validation

Conference Committees

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Conference Sponsors

Funding Agency
Funding Agencies
SIAM and the Organizing Committee wish to extend their thanks and appreciation to the U.S.National Science Foundation and DOE Office of Advanced Scientific Computing Research for their support.
Ways to Sponsor

SIAM invites you to show support of this meeting through sponsorship opportunities ranging from support of receptions, audio-video needs, to awards for student travel, and more.

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Thank you to our sponsors

Thank you to our conference sponsors

Thank you to our sponsors

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