Grow with Anabel

Anabel is a first-generation college graduate with an M.S. in Applied Mathematics from UC Irvine.

She brings a quantitative background in operations research with recent work spanning physics-informed neural networks, Monte Carlo simulation, and regression analysis. Anabel currently exploring opportunities in the defense, federal, and aerospace sectors, particularly around the Huntsville, Alabama area.

Her own path through higher education wasn't the traditional one, and that's shaped how she thinks about teaching: it should be accessible, patient, and built around the person in front of you, not a one-size-fits-all pace. That's why she tutors in math, from foundational skills through college-level coursework.

Projects

Advanced Studies

Academic Background

At UC Irvine, Anabel conducted applied mathematics research under the supervision of Dr. John Lowengrub. She earned her B.S. in Applied Mathematics with distinction from Sonoma State University in 2023, where she was a McNair Scholar, Cal-Bridge Scholar, and a member of Dr. Omayra Ortega’s Mathematical Epidemiology Research Group (MERG). These experiences strengthened her interest in interdisciplinary problem solving and research-driven work.

Research Focus

Her latest work focuses on physics-informed neural networks (PINNs), a class of deep learning models that incorporate physical laws directly into training. She applied these methods to inverse problems and scientific modeling, building computational pipelines that combine partial differential equations, optimization, and data-driven learning to improve interpretability and predictive performance.

Publications

Cabrera, S, Camarena, A, Hedge, N, Ochoa Zavalza, S, Tolson III, D, Williams, ME, Ortega, O.

“Using Linear Regression to Examine Bias in Home Valuation” Sonoma State McNair Scholars Research Journal. Rohnert Park, CA: Sonoma State University. 2023