Welcome to my portfolio website! Here are two of my favorite projects, and if you’d like to see more, you can find them in the top right corner.
Welcome to my portfolio website! Here are two of my favorite projects, and if you’d like to see more, you can find them in the top right corner.
In this project, we explored whether ensembling transformers or increasing model size improves news source classification. Using a curated dataset of 3,713 Fox and NBC headlines, we found that transformer ensembles outperformed the best individual models by 1.08%. In contrast, scaling up from BERT-base to BERT-xlarge did not improve performance, showing that model diversity is more effective than size for short-text classification tasks.
This is a Stirling Engine modeled as a hamster running in a wheel. The engine was designed in SOLIDWORKS and most parts were machined at UPenn's Precision Machining Laboratory using, Mill, Lathe, and CNC Operations.