Applied Mathematician & Computer Scientist
I'm an undergraduate student at Cal Poly San Luis Obispo studying applied mathematics and computer science with a strong interest in algorithmic problem-solving, machine learning, and applications of advanced theoretical mathematics to real-world problems. I am fluent in Python, C/C++, and Java, and have experience with machine learning libraries such as TensorFlow and PyTorch. I especially enjoy working on projects that combine advanced mathematics with performant software design.
I enjoy tackling complex problems and turning them into elegant, efficient solutions. Whether it's optimizing matrix multiplication programs or building quantitative trading models, I approach each project with analytical rigor and creative problem-solving.
Lately I've been tinkering with running LLMs locally to better understand how I can use them effectively, without data privacy concerns or rate limits. I also spend a lot of time reading about various branches of mathematics, parallel programming, scientific computing, financial mathematics, and astronomy.
In my free time, I enjoy rock climbing, hiking, simracing, cooking, and photography.
An MPI-based performance-oriented matrix multiplier and determinant calculator written in C.
Creating a trading model for Bitcoin and gold that maximizes profit using mathematical optimization.
Modeling the erosion of ancient stairs with quadric surfaces for the 2025 COMAP Mathematical Competition in Modeling.
A TensorFlow facial recognition model designed for the Spresense dev board. Submission for the 2025 CPES x Sony Hackathon.
A collection of parallelized C/C++ programs for manipulating, interpolating, and compressing bitmap images.
A high-performance, unproven primality test that uses the PSW algorithm. Optimized for speed to try and disprove the PSW conjecture.
A Python text embedding model that calculates lexical similarity using cosine similarity.