This event is part of Uncertainty Quantification and AI for Complex Systems View Details

Uncertainty Quantification for Material Science and Engineering

April 21 — 25, 2025

Description

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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.

Organizers

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W C
Wei Chen University of Buffalo
P C
Peter Chien University of Wisconsin-Madison
Y H
Ying Hung Rutgers, the State University of New Jersey
R J
Roshan Joseph Georgia Tech
L K
Lulu Kang University of Massachusetts, Amherst
T S
Taylor Sparks University of Utah

Speakers

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S B
Sterling Baird University of Toronto
W C
Wei Chen Northwestern University
A C
Aleksandr Chernatynskiy Missouri S&T
K C
Kamal Choudhary National Institute of Standards and Technology (NIST)
Y H
Ying Hung Rutgers University
S K
Surya Kalidindi Georgia Institute of Technology
Y L
Yifan Liu Oak Ridge National Laboratory
N P
Noah Paulson Argonne National Laboratory
B P
Bruce Pitman University at Buffalo
R S
Ralph Smith North Carolina State University
T S
Taylor Sparks University of Utah
A T
Anh Tran Sandia National Labs
L W
Liwei Wang Carnegie Mellon University
Y W
Yan Wang Georgia Institute of Technology
H Z
Houlong Zhuang Arizona State University

Schedule

Monday, April 21, 2025
9:00-9:30 CDT
Welcome/Breakfast/Check-in
9:30-10:15 CDT
Gaussian Process for Materials Research

Speaker: Bruce Pitman (University at Buffalo)

10:15-10:30 CDT
Q&A
10:30-11:15 CDT
Coffee Break
11:15-12:00 CDT
DiSCoVeR 2.0: Mutual Information Informed Novelty Estimation of Materials Along Chemical and Structural Axes

Speaker: Taylor Sparks (University of Utah)

12:00-12:15 CDT
Q&A
12:30-14:00 CDT
Lunch Break
14:00-14:45 CDT
UQ and atomistic simulations

Speaker: Aleksandr Chernatynskiy (Missouri S&T)

14:45-15:00 CDT
Q&A
15:00-15:30 CDT
Coffee Break
15:30-16:15 CDT
Accelerated predictions of the sublimation enthalpy of organic materials with machine learning

Speaker: Yifan Liu (Oak Ridge National Laboratory)

16:15-16:30 CDT
Q&A
Tuesday, April 22, 2025
9:00-9:30 CDT
Breakfast/Check-in
9:30-10:15 CDT
Combining reinforcement learning with graph convolutional neural networks for efficient design of TiAl/TiAlN atomic-scale interfaces

Speaker: Houlong Zhang (Arizona State University)

10:15-10:30 CDT
Q&A
10:30-11:15 CDT
Coffee Break
11:15-12:00 CDT
Latent Variable Approaches for Data-Driven Design of Heterogeneous Metamaterial Systems

Speaker: Liwei Wang (Carnegie Mellon University)

12:00-12:15 CDT
Q&A
12:30-14:00 CDT
Lunch Break
14:00-14:45 CDT
Computational Statistics Meets Materials Science: Advances in UQ, OED, and SciML

Speaker: Anh Tran (Sandia National Labs)

14:45-15:00 CDT
Q&A
15:00-15:30 CDT
Coffee Break
15:30-16:15 CDT
Learnings from Uncertainty Quantification in Computational Thermodynamics

Speaker: Noah Paulson (Argonne National Laboratory)

16:15-16:30 CDT
Q&A
Wednesday, April 23, 2025
9:00-9:30 CDT
Breakfast/Check-in
9:30-10:15 CDT
Towards a Digital Twin Framework with Uncertainty Quantification: Machine Learning, Bayesian Optimization and Model Predictive Control

Speaker: Wei Chen (Northwestern University)

10:15-10:30 CDT
Q&A
10:30-11:15 CDT
Coffee Break
11:15-12:00 CDT
Parameter Subset Selection and Active Subspace Techniques for Models in Engineering, Material Science, and Biology

Speaker: Ralph Smith (North Carolina State University)

12:00-12:15 CDT
Q&A
12:30-14:00 CDT
Lunch Break
14:00-15:15 CDT
Panel for National Academies study “Frontiers of Statistics: 2035 and Beyond”
15:15-15:30 CDT
Coffee Break
15:30-16:15 CDT
A (somewhat) gentle introduction to Bayesian optimization for materials

Speaker: Sterling G. Baird (University of Toronto)

16:15-16:30 CDT
Q&A
Thursday, April 24, 2025
9:00-9:30 CDT
Breakfast/Check-in
9:30-10:15 CDT
Accelerated materials innovation using AI/ML and Digital Twins

Speaker: Surya Kalidindi (Georgia Institute of Technology)

10:15-10:30 CDT
Q&A
10:30-11:15 CDT
Coffee Break
11:15-12:15 CDT
Lightning Talk Session
12:30-14:00 CDT
Lunch Break
14:00-14:45 CDT
Physics-Constrained Bayesian Neural Networks to Predict Grain Evolution

Speaker: Yan Wang (Georgia Institute of Technology)

14:45-15:00 CDT
Q&A
15:00-16:00 CDT
Poster Session
Friday, April 25, 2025
9:00-9:30 CDT
Breakfast/Check-in
9:30-10:15 CDT
Identifying Nonlinear Dynamics with High Confidence from Sparse Data

Speaker: Ying Hung (Rutgers, the State University of New Jersey)

10:15-10:30 CDT
Q&A
10:30-11:15 CDT
Coffee Break
11:15-12:00 CDT
Uncertainty Analysis of Materials AI Models using the JARVIS-Leaderboard

Speaker: Kamal Choudhary (National Institute of Standards and Technology (NIST))

12:00-12:15 CDT
Q&A

Poster Session

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Posters that have been submitted in advance of the event can be viewed on the Poster Session page.

Registration

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IMSI is committed to making all of our programs and events inclusive and accessible. Contact [email protected] to request disability-related accommodations.

In order to register for this workshop, you must have an IMSI account and be logged in. Please use one of the buttons below to login or create an account.