I am currently in my last semester of studying Computer Science at the University of St. Thomas, MN. In July 2023 I will start full-time with Optum in their Technology Development Program as an associate software developer.

I started coding during my freshman year of college and have loved it ever since. My favorite courses have been my security, web development and AI/ robotics courses for their content and wide range of skills that I learned in them.

I am from Chanhassen, Minnesota and in my free time I enjoy being either outside exploring, camping, playing sports (🏈⚾🏀🏐), or just doing random other things in the sun or snow. I also enjoy playing video games or just chatting with friends.

Since I have not been coding for too long, my list of projects is still in its early stages but here are the three that I am most proud of.

Soapi is an open source, automated data preprocessing library that I made with my internship group this last summer with Optum. It was developed in Python with help from Jupyter Notebooks along with the Pandas, Pandas Profiling, Numpy, and Scikit-learn libraries.

The process of data preprocessing is taking raw data with all of its missing, irrelevant, and categorical cells and transform it into a database that has only relevant rows and columns that are all filled in. These rows were filled in based on the preference of the user to either use the row's mean, median, or mode or to fill it in with a placeholder to signify that it is a formerly empty cell. Once this process is complete, our library allows the user to transforming the categorical data into numerical data which is helpful because machine learning can process numbers a lot faster than it can process categorical data and they take up less space. Lastly our program can translate these numbers back into their original categorical values for use once the machine learning algorithm returns numerical results/ predictions.

Although it is not officially published on the pypi website where python packages can be downloaded by anybody, we did publish it on the testpypi website which is where open source python libraries can be "soft published" for testing by people with the link and so it can be installed with the following command:
pip install --extra-index-url https://test.pypi.org/simple/ soapi

This project is one from Computer Graphics with some starter code that I worked on with two other students. I have a more in depth README in the project repository, but I am proud of this project because it took two tools that I had next to no prior experience with, JavaScript and matrix multiplication. The project was to create models of polygons on a 2D plane as though they were in 3D space which we did by calculating, with matrix multiplication, where the point would appear to the human eye's perspective and placing it there on the 2D plane and drawing a line between the two points. I am also proud that we were able to create the functionality to allow the user to use one central point and the program will calculate the rest of the model's points and lines.

In my Computer Architecture class, we were tasked to code a virtual CPU that progressively moved toward a CPU's functionality in 2000 with each assignment and this portion of the project reflects the implementation of pipelining. I worked on this with Tara Sothy with some starter code from Dr. David Myre.

Pipelining in computer architecture is the taking advantage of the fact that each step takes a certain amount of time and starting processes while current resources are free despite future ones being in use. Taking laundry as an everyday example. Saying it is a 5 step process of collecting, washing, drying, folding, and sorting. If someone had two loads to do it would be a long, tedious task of waiting for the entire first load to go through the whole process and so instead once the laundry is out of the washing machine, you should put the next load in to avoid wasting resources (washer, dryer, etc) and to make the overall task go as quick as possible. Inside the CPU, the same thing is happening but on a code level with each instruction of code and that is what is reflected in this project.