About Me

I am a Mathematics PhD Candidate at the University of Nebraska-Lincoln (expected December 2026), advised by Eloísa Grifo. My research focuses on neural ideals in commutative algebra, with the aim of applying these algebraic tools to analyze deep learning models, bridging pure mathematics with practical machine learning applications.

Since 2024, I have been a Research Intern at the Georgia Tech Research Institute, where I develop machine learning solutions for defense-oriented research programs. My work there includes designing deep learning models for anomaly detection and classification, processing large-scale datasets, and applying mathematical frameworks like sheaf theory to network security analysis.

I hold a BS in Applied Mathematics with minors in Computer Science and Spanish from Missouri State University, along with an MS in Mathematics. My technical background spans Python (PyTorch, TensorFlow, scikit-learn), C++, SQL, and computational algebra systems. I am driven to apply my mathematical and computational expertise to national security challenges, particularly in geospatial intelligence, pattern recognition, and data-driven analysis.

Outside of work, I enjoy crocheting, reading, and spending time with my dog, Lulu. I am originally from St. Louis, Missouri.

I was previously known as Sabrina Klement.