Clarkson Students Win NSF Fellowships for Mechanistic Machine Learning Research | Clarkson University
Matthew Lukaszewski ‘23 and Alek Ahrens ‘23 have been awarded National Science Foundation (NSF) Fellowships for Mechanistic Machine Learning research they have been conducting with Assistant Professor of Civil and Environmental Engineering Behzad Behnia. This NSF project is focused on the use of spiral cracking patterns in fracture characterization of soft adhesive materials.
“Matthew and Alek are both software engineering students and they have been helping me with the computational part of this NSF project where I am trying to apply computer vision in conjunction with machine learning and deep learning algorithms to develop a data-driven automated fracture pattern characterization of infrastructure materials. We try to use machine learning algorithms to find patterns in cracking data that would allow us to build descriptive or predictive models and to automatically find non-obvious, complex relationships between data that, otherwise, are usually found by an extensive knowledge of the problem,” Behnia said.
This fellowship is offered by the NSF to both graduate and undergrad students who are involved in mechanistic machine learning research-type projects. As part of their fellowship, Alek and Matthew will get to attend the 2021 Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (MMLDT-CSET) conference which will be held in San Diego in late September
“Matthew and Alek are both software engineering students and they have been helping me with the computational part of this NSF project where I am trying to apply computer vision in conjunction with machine learning and deep learning algorithms to develop a data-driven automated fracture pattern characterization of infrastructure materials. We try to use machine learning algorithms to find patterns in cracking data that would allow us to build descriptive or predictive models and to automatically find non-obvious, complex relationships between data that, otherwise, are usually found by an extensive knowledge of the problem,” Behnia said.
This fellowship is offered by the NSF to both graduate and undergrad students who are involved in mechanistic machine learning research-type projects. As part of their fellowship, Alek and Matthew will get to attend the 2021 Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (MMLDT-CSET) conference which will be held in San Diego in late September
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