Projects

Survival Analysis of Lung Cancer Data for Non-Invasive Cancer Detection

Survival Analysis of Lung Cancer Data for Non-Invasive Cancer Detection

Technologies: Python, Sci-kit Learn, Pandas, Numpy, Matplotlib, Seaborn, Skurv, Lifelines

My senior capstone research project. I researched the potential of a novel DNA sequencing method called DELFI to predict lung cancer patient survival times and outcomes.

Online Retail Analysis

Online Retail Analysis

Technologies: Python, Pandas, Matplotlib, Seaborn, Scikit-learn

Modeled the unit price of items based on the quantity of items purchased. Used the K-means clustering algorithm to segment customers based on their purchasing behavior. Compared several regression methods including linear regression, decision tree regression, and ensemble methods

Bayesian Clinical Heart Failure Prediction

Bayesian Clinical Heart Failure Prediction

Technologies: R, ggplot2, dplyr, stanglm, brms

Predicted clinical survival status of clinical heart failure patients using traditional regression methods to predict time till death. Modeled bayesian regression models to predict time till death and logistic regression to predict death event status.

Chinese MNIST Drawing Classification

Chinese MNIST Drawing Classification

Technologies: Python, Pytorch, Fastapi, Next.js, Docker, Tailwind.css, Azure

Classified hand drawn Chinese digits using convolutional network. Used as a tool to teach myself how to use deep learning models in production and practice my chinese.