Announcements of Opportunity
SURF: Announcements of Opportunity
Below are Announcements of Opportunity posted by Caltech faculty and JPL technical staff for the SURF program. Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor. Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions!
Remember: This is just one way that you can go about identifying a suitable project and/or mentor. Click here for more tips on finding a mentor. Announcements for external summer programs are listed here.
*Students applying for JPL projects should complete a SURF@JPL application instead of a "regular" SURF application.
*Students pursuing opportunities at JPL must be U.S. citizens or U.S. permanent residents.
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| Project: | When Digital Image Correlation Meets Machine Learning | ||||||||
| Disciplines: | Mechanical Engineering, Civil Engineering, Aerospace Engineering | ||||||||
| Mentor: |
Jin Yang,
Assistant Professor, (EAS),
jin.yang@austin.utexas.edu, |
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| Mentor URL: | https://sites.utexas.edu/yang/ (opens in new window) | ||||||||
| Background: | NOTE: This project is being offered by a Caltech alum and is open only to Caltech students. The project will take place at the University of Texas, Austin, in Austin, Texas. | ||||||||
| Description: | Leveraging state-of-the-art machine learning and data-driven methods to improve 2D and 3D full-field deformation measurement (e.g., digital image correlation, digital volume correlation, particle tracking) and other material characterization experimental techniques. Students will perform either hands-on mechanical characterization experiments or develop state-of-the-art machine learning-based computational methods. | ||||||||
| References: | https://sites.utexas.edu/yang/research/ | ||||||||
| Student Requirements: | Linear Algebra, Calculus, Statics, Dynamics, Mechanics of Solids, Finite element method, Machine Design, Experimental Methods | ||||||||
| Programs: |
This AO can be done under the following programs:
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