About Me
I'm Brendan Connelly, a mathematics major at UCLA with diverse interests across pure and applied mathematics. My current research projects are in quantitative finance and combinatorics, and my published paper describes an intrinsic rank estimation and NMF pipeline for analyzing frequency comb data.
My coursework includes graduate-level complex analysis, differential geometry, optimization, and data science for finance, complemented by extensive study in real analysis, abstract algebra, and probability theory. I enjoy tackling complex problems that bridge theoretical mathematics with computational applications.
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