Portfolio
Source: NASA/JPL-Caltech/ESA/Harvard-Smithsonian CfA Determining Importance of Features Related to Star Formation in Central and Satellite Galaxies Using Machine Learning
My latest research involves exploring how to best utilize supervised ML models to classify spatially resolved pixels and predict their star formation rate.
Source: NASA, JPL-Caltech, Susan Stolovy (SSC/Caltech) et al. Celestial Body Classification Using Neural Networks
A personal project to classify celestial bodies using a feedforward neural network. The dataset was obtained from the Sloan Digital Sky Survey (SDSS) and contains data on galaxies, stars, and quasars.