This workshop will explore the crucial role of uncertainty quantification (UQ) in advancing materials research and development. Participants will explore the unique challenges of uncertainty quantification (UQ) and machine learning in materials science, such as multi-scale modeling, energy prediction, complex material property modeling, and additive manufacturing. The workshop will cover surrogate modeling techniques tailored for materials science simulations, such as Gaussian processes and neural networks and their application in optimization strategies for accelerated materials discovery. Additionally, attendees will explore cutting-edge machine learning tools for materials informatics, including feature selection, dimensionality reduction, and interpretable models for scientific insights. Through interactive lectures and group discussions, participants will gain practical skills in implementing UQ techniques and leveraging machine learning for material property prediction. This workshop will benefit statisticians, data scientists, and applied mathematicians working on UQ for materials applications, as well as material scientists and engineers who are interested in applying UQ methods to the materials domain. By the end, attendees will be equipped with the knowledge and tools to enhance their research and stay at the forefront of materials science and engineering.
Funding
Priority funding consideration will be given to those to register by February 20, 2025. Funding is limited.
Poster Session
This workshop will include a poster session. In order to propose a poster, you must first register for the workshop, and then submit a proposal using the form that will become available on this page after you register. The registration form should not be used to propose a poster.
The poster proposal deadline is March 23, 2025. If your proposal is accepted, you should plan to attend the event in-person.
IMSI is committed to making all of our programs and events inclusive and accessible. Contact [email protected] to request disability-related accommodations.
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