Data Science Student | Aspiring Data Scientist/Analyst
Transforming data into actionable insights through machine learning, statistical analysis, and creative problem-solving.
I'm a Data Science student at the University of Wisconsin–Madison with a strong foundation in computer science and a passion for turning data into meaningful, real world insights. My academic work and personal projects focus on data analytics, machine learning, and applied problem solving, with hands-on experience using Python, SQL, Pandas, PyTorch, and data visualization tools.
I'm especially interested in roles where analytics directly support healthcare, product development, or business decisions, and I value environments that encourage collaboration, curiosity, and continuous learning. I'm currently seeking data analytics or data science internships where I can apply my skills, learn from industry professionals, and contribute to innovative, data-driven teams.
When I'm not analyzing datasets or building models, I enjoy lifting, playing basketball, watching movies and fishing.
Expected Graduation
Projects Completed
Technical Skills
A selection of projects showcasing my data science/computer science skills and problem-solving abilities
Developed a brain tumor classifier achieving 96% accuracy after discovering and mitigating dataset bias through Grad-CAM analysis and iterative preprocessing validation. Applied advanced techniques including batch normalization, dropout regularization, early stopping, and differential learning rates to prevent overfitting.
Deployed a production-ready review sentiment classifier as interactive web application using Streamlit and GitHub, enabling real-time sentiment analysis across movies, restaurants, and products.
Built a customer churn prediction model achieving 84.6% ROC-AUC on 7,043 telecom customers, identifying high risk segments and translating insights into data-driven retention strategies with a projected annual savings of $467K-$700K. Deployed a live demo using Streamlit for stakeholder engagement.
I'm always open to discussing new opportunities, collaborations, or just chatting about data science!