Deep Learning (CNNs & PyTorch)
Model design, training loops, evaluation, and practical computer vision workflows.
Astronomy & Astrophysics • Planetary Science
Open to: internships • research roles
I'm an undergraduate astrophysics and planetary science major at Florida Tech researching the utilization of deep learning models in astronomical studies. This site collects my projects, resume, and contact info. Please feel free to reach out.
Completed courses that directly support my interests in astronomy, physics, and machine learning.
Model design, training loops, evaluation, and practical computer vision workflows.
Lagrangian/Hamiltonian methods, constrained systems, and analytical problem solving.
Separation of variables, eigenfunction expansions, and boundary value problems.
Quantum/relativity fundamentals, atomic & nuclear topics, and applied problem sets.
Stellar structure/evolution, observations, and interpreting survey-style datasets.
Telescope/CCD instrumentation fundamentals, calibration & noise, and hands-on coding projects for astronomical data reduction and analysis.
Selected projects with links to pages, datasets, and technical writeups.
Object detection and live target classification
Spectral classification and stellar type prediction
Smaller utilities, experiments, and side projects I've performed.
Instrumentational code used to calculate the recommended exposure time based on cloud seeing, SNR, etc.
ViewExtremely rudimentary college project I found interesting.
ViewSmall multi-paged site coded on github as an introduction into new languages.
View