Data Pipelines | Machine Learning | Computer Science Graduate
I'm a recent computer science graduate with hands-on experience in Python automation, large-scale data processing, GPU accelerated machine learning workflows, and cloud-adjacent DevOps environments.
With experience in Python, SQL, and data visualization, I specialize in discovering hidden patterns and trends in data. This portfolio showcases my projects across various projects.
Utilizing simulated VIIRS IR data over a natural range of parameters, we trained a neural network model to quantify dust in the atmosphere. After evaluating the model skill on the simulated test dataset, we applied the neural network to actual VIIRS images of a visible dust event also captured by AERONET.
A mock online car buying platform, that I created for my Database Design class.