Research Assistant at California State University, Fullerton
Yorba Linda, California, United States
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Summary
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Senior
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Alexandra Macedo is a research-focused software engineer with nine years of experience building high-performance scientific software for gravitational-wave physics and detector characterization. As a research assistant at CSUF’s GWPAC and collaborator with Caltech and the international SXS team, she has contributed core C++17 back-end work to SpECTRE—implementing expressive tensor libraries and Einstein-equation evolution systems used in numerical relativity simulations of black hole and neutron star mergers. She pairs a strong academic foundation (MS in Computer Science from UCSD, MS work in Physics at CSUF, and a UCLA BS in biology) with practical engineering: automated grading systems for large CS courses and ML-driven noise characterization tools for LIGO. Colleagues know her for translating mathematical notation into clean, efficient code interfaces that make complex tensor algebra more ergonomic and performant.
9 years of coding experience
2 years of employment as a software developer
University of California, San Diego
Bachelor of Science (B.S.), Molecular, Cell, and Developmental Biology, GPA: 3.60 overall, 3.97 major, Bachelor of Science (B.S.), Molecular, Cell, and Developmental Biology, GPA: 3.60 overall, 3.97 major at University of California, Los Angeles
General coursework, Computer Science and Physics, 3.92, General coursework, Computer Science and Physics, 3.92 at California State University, Fullerton
SpECTRE is a code for multi-scale, multi-physics problems in astrophysics and gravitational physics.
Role in this project:
Back-end Developer
Contributions:461 reviews, 143 commits, 100 PRs in 2 years 3 months
Contributions summary:Alexandra primarily contributed to the core data structures and expression evaluation within the SpECTRE code. Their commits focused on enhancing the tensor expression library with features such as improved template metaprogramming for optimized arithmetic operations and complex data structures using C++17 and later. These efforts involved significant modifications to tensor expressions and mathematical operations, improving overall efficiency and expressiveness of the code. The user also implemented improvements to internal data types and algorithms.
Contributions:63 pushes, 19 branches, 1 comment in 1 year 9 months
characterizationpython-utilitiespythondetector
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Alexandra Macedo - Research Assistant at California State University, Fullerton