- Developed all curriculum, course material, and independently taught all sections of AP Physics I and II with no other AP Physics teachers.- Served as faculty sponsor for two campus organizations: Robotics Club and Astrophysics & Aerospace Club, providing detailed afterschool instruction relating to coding and astronomy.

Designed and completed various technical research projects including:- Personally operated university telescopes to obtain, process, and analyze photometric images of star cluster NGC 6633, statistically comparing stellar brightnesses and colors to typical stellar populations to obtain a precise distance estimation in high agreement with literature values. (Python, Unix, SQL)- Used Markov-chain Monte Carlo methods to analyze high-resolution radio interferometric images of protoplanetary disk HD163296, a disk of gas and dust surrounding a newborn star, to obtain spectral data revealing radial temperature, dust density, and dust size profiles. (Python, Unix)- Built and trained a convolutional neural network to quickly and autonomously identify solar flares using thousands of live solar images from the Solar Dynamics Observatory satellite. (Python [Pytorch], Unix [Google Drive API], git/github)- Undergraduate thesis: Processed and analyzed raw radio interferometric data from the most advanced telescope array in the world (ALMA) to produce the highest resolution radio image of protoplanetary disk LkCa 15 to date, proving the existence of a previously proposed third ring and searching for evidence of the second-ever observed accreting protoplanet. (Python, Unix)

Utilized Los Alamos high-performance supercomputing resources to model ring formation and dust growth in protoplanetary disks, large disks of gas and dust surrounding infant stars. Conducted high-dimensional parameter searches using viscosity dead zones to produce rings matching those of observed protoplanetary disks HD163296 and HD169142, attempting to constrain temperature, dust size, and dust density estimates in the disk as a function of radial distance from the star.

Used Los Alamos proprietary hydrodynamic protoplanetary disk simulations to model dust density and size growth in protoplanetary disk rings, finding strongly linear relationships between disk parameters such as total disk mass and maximum dust grain size before fragmentation.

- Implemented and evaluated a newly proposed randomized QR decomposition algorithm in MATLAB for deblending and denoising seismic data with strongly overlapping waveforms, testing the algorithm against industry-standard synthetic data, and observing an immense speed increase of up to 50x faster than previous methods with no loss in output quality. - Researched and implemented alternative fast Eigenimage Filtering, Principal Component Analysis (PCA), and Singular Spectrum Analysis (SSA) methods of deblending seismic data, investigating the algorithms’ speed and efficacy in comparison to randomized QR decomposition. - Also investigated and tested the potential efficacy and feasibility of automated parameter selection, enabling small gains in algorithmic efficiency.

Proofread, edited, and wrote solution manuals for practice SAT and ACT exams. Made eligible for the position by earning a perfect SAT score in 2015.