Projects
This project entailed the use of machine learning and statistical methods to classify fuel sources of wildfires using 1-meter resolution aerial imagery.
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Using the The Greenhouse Gas inventory data from the United Nations on the UNData site, I created a visualization that shows the GHG emissions for each country in the data set. I used this to create a Streamlit app so the user can choose a country and see the emissions from 1990 to 2017.
Using the Surface Soil Wetness data from the NASA POWER data set, I created and managed a SQL database and used it to make visualizations and time series analysis. Using Streamlit, I created an interactive Choropleth map that demonstrates how wet or dry the soil in all of the California counties are. I also applied statistical and seasonal analysis on the time series data.
During this Astrophysics project, I created FOAMS. FOAMS is a programs that takes a user input of abundance observations from celestial objects and fits those abundances using simulated nucleosynthesis models from supernovae and AGB stars.
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