Internet memes are often viewed as entertainment, but they can also shape political discussion and public opinion. In this project, I examined how political memes on Reddit responded to major political events between 2020 and 2025. Using topic modeling, time-series analysis, and machine learning techniques, I identified recurring themes in thousands of memes and analyzed how their frequency changed in response to real-world events. By studying humor as a form of political communication, this work explores how online communities frame policy issues and influence public engagement through satire and shared narratives.

Stroke remains one of the leading causes of death and long-term disability worldwide, making accurate prediction of patient outcomes an important medical challenge. In this project, I applied machine learning techniques to clinical datasets to identify patterns associated with stroke prognosis and patient survival. By developing predictive models and evaluating their performance across diverse populations, I explored how data science can support clinical decision-making and help physicians provide more personalized care for patients at risk.