Implemented 4 versions of a basic Neural Network using Tensorflow to predict cab fares for every time bracket of the day with 4 different data cleaning methods, resulting in the best output of a Root Mean Squared Error of 2.7 among the 4, placing it in the top 5 Kaggle submissions among almost 1500 submissions.

Developed a network of student interactions in classrooms using stochastic block models and the NetworkX library in Python, and implemented an SIR model in Javascript using networks in D3 to animate 10 weeks of coronavirus spread.

Developed a simple optimization library in Python to implement several optimization algorithms like gradient descent, Newton’s method, and conjugate-gradient methods.

Scraped twitter feeds of all US Presidential Candidates, and generated Personality Insights using IBM Watson's Personality Insights API. Also developed interactive bubble and bar charts using ChartJS, along with front-end component to display information about personality traits and keywords most frequently used by candidates

Used QGIS to plot public schools and oil wells and create buffers of overlapping regions. Also created a choropleth map showing correlation between income distribution and the likelihood of a school being near an oil well