Computational engineer focused on aerospace simulation, scientific software, and numerical validation.
- B.S. in Computational Engineering, The University of Texas at Austin (2026)
- Python, C++, and MATLAB development on Linux
- Numerical methods, orbital mechanics, backend APIs, testing, and containerized workflows
A Flask API that processes NASA's public ISS OEM ephemeris, exposes orbital state vectors, and derives speed and Earth-relative location. The repository includes deterministic tests, explicit error handling, Astropy frame transformations, and reproducible local and container workflows.
A C++17/MPI simulation comparing direct all-pairs gravity with a three-dimensional Barnes-Hut approximation. It documents the replicated-data architecture and numerical limitations, includes deterministic core tests and two-rank MPI smoke tests, and presents performance and momentum-drift measurements collected on the Frontera supercomputer.
Two deliberately separate astrodynamics modules: a universal-variable two-body propagator covering elliptic, parabolic, and hyperbolic motion, and an Earth ground-track/observer-visibility tool. Reconstructed results are tied to archived coursework evidence, cross-checked against ode45, and validated in GNU Octave CI.
An independently implemented Flask, Redis, Docker, and Kubernetes platform for New York gasoline-price data. The API, queue worker, and deployment topology are tested separately and together, including a full container smoke test from HTTP request through Redis to asynchronous result.
| Area | Repository evidence |
|---|---|
| Scientific Python and APIs | ISS ephemeris parsing, Astropy frame transforms, Flask routes, deterministic fixtures, and container runtime checks |
| C++ and parallel computing | MPI data distribution, direct and Barnes-Hut gravity, CMake, core tests, and Frontera benchmark results |
| Numerical methods and astrodynamics | Universal variables, adaptive-integration comparison, orbital coordinate transforms, regression values, and explicit model limits |
| Distributed systems and deployment | Versioned API, Redis queue and persistence, independent worker, Docker Compose, hardened Kubernetes manifests, and end-to-end CI |
I care about explicit assumptions, validation against known ground truth, reproducible setup, and documenting the limits of what a model or test actually proves.