I’m a recent B.S. in Computer Science graduate with a strong focus on generative deep learning and MLOps. I have multiple years of undergraduate research experience building and training deep learning models, along with hands-on experience deploying models using Docker, TensorFlow Serve, and cloud infrastructure. I enjoy working across the full pipeline—from data and experimentation to production-ready systems.
Note: Due to compute limitations of the server this website is hosted on, generation will take a few minutes.
A 9M parameter causal language model trained on the TinyStories dataset to complete short children's stories.
The presence of noise in a signal can render that signal useless. I solve this problem by implementing a variational autoencoder to encode electrocardiogram signals. I then use a neural network to classify the encoded data, achieving a balanced accuracy of 76% across 3 noise classes.

This website was built to showcase my full-stack development skills. It also showcases my systems engineering and MLOps abilities by building a custom Docker container for this website software, as well as connecting it to my proprietary SAM-1 model for showcasing generation abilities. All of which is hosted on a single server for cost-efficiency.