Gravitation & Cosmology
Black Hole Mechanics
This graduate-level course was taken as an elective in an attempt to learn more about spacetime geometry. As a final for the course, I paired up with an astrophysics PhD candidate to conduct a presentation and independently wrote a paper on Black Hole Mechanics. This paper included a discussion on the different black hole metrics where I was first introduced to the cosmic censorship conjecture. I am excited to explore more on this topic in my graduate studies. I also included a comparison of the laws controlling black hole dynamics and the laws of thermodynamics. Both the paper and presentation can be found on GitHub here or downloaded below.
Linear Optimization
Optimal Delivery Route for Assurance Delivery
This course fulfilled a Capstone requirement with the opportunity to choose an optimization problem for a fictitious company. I chose to solve a graph-based minimization problem using Python to find an optimal delivery route based on traffic and distance conditions. Additionally, I created a Graphic User Interface shown on the right that can be used by drivers to find the optimal route while on the go. With these conditions, I conducted a cost and risk analysis to allow users to manipulate the amount of risk they are willing to acquire based on the size of the order and distance driven. All code and the full report can be found on GitHub here or downloaded below.
Mathematical Computing
An Analysis of Optimal Soil Choice
This course fulfilled a requirement for my degree in theoretical mathematics. This project was a final group project completed with two mathematics graduate students. We conducted data analysis on two sets of plant growth data from a fictitious company. Each plant was grown in a specific fertilizer, and we had to analyze which fertilizer the company should choose to grow their plants in. Using Python, we used curve fitting as shown on the left and prediction techniques to compute the optimal choice based on specific company parameters. We also conducted a risk analysis to minimize excessive cost. All code and the full report can be found on GitHub here or downloaded below.