Research

My research interests are at the intersection of ultrasonic non-destructive evaluation and machine learning. Recently I have been working on physics informed machine learning approaches for modeling Lamb Waves in different media and analyzing its ability to explore defects for non-destructive evaluation. My secondary passion for studying these problems are the connections with analysis, linear algebra, and partial differential equations.

These days my goals in research can be separated into two major projects

[Ultrasonic Non-Destructive Evaluation] I work in collaboration with TRI-Austin, affiliated with the air force, with deep learning approaches for defect detection.

[Physics Informed Machine Learning] Studying fractional partial differential equations and their modeling implications for anisotropic waves related to non-destructive evaluation.

I am advised by Dr. Joel Harley with the immense thanks for the independence and rediscovery of the joy of learning during my time with him.

In the past I have worked on various deep learning projects for neurodegenerative diseases from retinal imaging, primarily Alzheimer’s Disease and Parkinson’s Disease. I have a general background in neuroscience, medical imaging (primarily MRI, and some minor depth in fMRI, CT, PET, etc.) as a consequence. I have also done work in more for more general eye diseases (glaucoma, diabetic retinopathy, etc.).