Computer Science

My education at Illinois Institute of Technology has expanded my capacity to create epic software using optimal data structures and slick algorithms. I am expected to complete my Master's in Computer Science in May 2019.

Programming Languages

  • SQL: Expert
  • C/C++: Expert
  • PHP: Expert
  • Java: Expert
  • Python: Proficient
  • VB.NET: Proficient
  • JavaScript: Familiar
  • GLSL: Familiar
  • Lua: Beginner

What I'm Learning Now

Virtual Machines

The use of cloud and container technologies has exploded over the last decade. Virtual Machines allow us to keep a common abstraction for easier deployment and increased compatibility. In this class I am writing an emulator for the MOS 6502 chip, my own JVM, and a container system.

Machine Learning

Having computers learn analagously to the way humans do opens up the programming paradigm of machine learning. From face recognition to medical diagnosis, there are many practical ways to make the model of machine learning useful. In this class I am learning various ML methods, including reinforcement learning, supervised learning, and deep learning.

Design and Analysis of Algorithms

This is my third and final class in algorithms. In this course, I will continue to expand my toolbox of problem solving methods, adding amortized analysis, Splay trees, Fibonacci heaps, fast Fourier transform, and approximation algorithms.

Computational Algebraic Geometry

In this class I am learning a way to connect algebra with geometry in order to solve systems of equations in multiple variables. I am writing algorithms in Macauley2 to generate Grobner Bases as well as a summarizing research paper that explains how to use Grobner bases to formulate phylogenetic trees.