I enjoy working on projects that bridge pure mathematics with practical applications, particularly in areas involving algebraic structures, geometric visualization, and mathematical education. I also have significant experience in mathematical biology and disease modeling. I have conducted research using physics-informed neural networks to model HIV infection dynamics as a member of the SDSU Disease Modeling Lab.
Currently, I'm interested in LLM-assisted theorem proving in Lean 4, including both autoformalization and direct proof synthesis from formal statements. My goal is to explore how language models can accelerate mathematical formalization and verification workflows. I spend much of my time working on these types of problems.
High-performance wrapper around pyFFTW with automatic optimization and drop-in NumPy/SciPy FFT replacement.
Pure Python library for solving polynomial systems using numerical homotopy continuation methods.
Python library for generating and manipulating mazes with various algorithms and customization options.
LaTeX template for making your documents look like old parchment paper.