About Me
I am a mathematics major at UCLA with interests spanning pure mathematics, applied mathematics, and computation. My current work includes research in quantitative finance and combinatorics, along with a published project from the UCLA CAM REU on intrinsic rank estimation and nonnegative matrix factorization for frequency comb data.
I have taken advanced coursework in areas such as complex analysis, differential geometry, optimization, real analysis, abstract algebra, probability, and machine learning for finance. Across these areas, I am most interested in problems where mathematical theory can be used to build, analyze, or improve computational methods.
Published Research: "NMF regularization techniques for unmixing frequency comb data" — Proc. SPIE 13920, Quantum Sensing, Imaging, and Precision Metrology IV, 139200Y (March 2026).
My Work
Course Notes
Detailed lecture notes on topics such as real analysis, abstract algebra, and more. Find my organized thoughts and explanations here.
Projects & Research
Explore my research and projects, including published work on computational methods and mathematical finance applications.
Resume
View my current resume in PDF format.
Homework
Selected homework assignments showcasing my problem-solving skills and thought process in various subjects.
Contact & Links
Email: brendanconnelly (at) ucla (dot) edu