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[July 28] USNCCM15 Short Course on Machine Learning Data-Driven Discretization Theories, Modeling and Applications

Zeliang Liu's picture

Dear Colleagues and Friends,

We cordially invite your participation in a short course “Machine Learning Data-Driven Discretization Theories, Modeling and Applications” as part of the pre-congress activities of 15th U.S. National Congress on Computational Mechanics Conference to be held on July 28, 2019 at Austin, Texas.

In this short course, we will introduce the participants to the latest efforts on data-driven methods for mechanical and material sciences. The course will cover topics on mechanistic data-driven clustering methods, direct and reduced order modeling techniques, physics-informed neural networks, multi-fidelity Gaussian processes, deep material networks and multiscale material failure analysis. Some benchmarks on nano-polymer composites, polymer matrix composites, additive manufactured alloys will be demonstrated. For more details, please visit the website, http://15.usnccm.org/sc15-005.  

The course number of this short class is SC15-005. You may register for this short course while registering for the congress at the USNCCM15 website:

http://15.usnccm.org/registration_information. 

This is a great opportunity for researchers, graduate students and post docs who are interested in studying how machine learning techniques are used in mechanics and mechanical science. Please also share the information with your colleagues and friends. We look forward to your participation!

Short Course Organizers

W.K. Liu, Northwestern University, USA, w-liu@northwestern.edu

George Karniadakis, Brown University, USA, George_Karniadakis@brown.edu

C.T. Wu, Livermore Software Technology Corporation, USA, ctwu@lstc.com

Zeliang Liu, Livermore Software Technology Corporation, USA, zlliu@lstc.com

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