This is a web dashboard I developed that uses the Method of Relaxation for approximating solutions to laplace's partially differential equation. This dashboard can be used to visualize the potential between a system of capacitors.
NOTE: This project is hosted on Heroku's Free Tier. This tier uses serverless hosting which may result in the app taking 10-20 seconds to load.
This is a web dashboard I developed that allows users to interactively view results from a Neutron Scattering Experiment. Functionally, the application allows for users to specifiy a sweeping direction, and interactively displays cross sections of a heatmap. The heatmap displays Neutron intensity data.
This is a program I developed for finding, tracking, and fitting Lorentzian peaks in data. This program allows the user to interactively preprocess data, and modify the parameters used for performing peak operations. I developed this application for doing data analysis and visualization on experiments that make use of Resonant Ultransonic Spectroscopy.
This is a command line application that allows for a user to bulk rename files using an editor such as vim! Why waste time writing scripts to rename files when you can use this program in conjunction with bulk text editing tools in your favorite editor?!
This application consists of a Jupyter Notebook I developed that gives a detailed explanation on how Random Forests work. I developed the Random Forest algorithm using the Python libraries Numpy and Pandas. In this notebook, I show how the algorithm can be used to investigate the relationship between personality types and substance abuse.
This is the website that you are currently looking at! I developed this website using Bootstrap for the frontend, and Python's Flask framework with Jinja2 templating for the backend. The program runs on the AWS LightSail service using the nginx webserver and the gunicorn application server.
This is a final project that I developed for a class on parallel programming. For this project, I developed three different implementations of the decision tree algorithm in C++, and analyzed the performance of each of the algorithms using Python. I than wrote a report comparing the runtime performance of each of my implementations under different thread counts that explains the observed behavior.