RxData Hub

Designed a dynamic visualization tool to track and analyze key performance metrics. While built on general datasets, this flexible framework is optimized to be adapted for healthcare environments—perfect for monitoring patient vitals, hospital KPIs, or inventory levels.

Developed a machine learning classifier to distinguish between malignant and benign tumors with high accuracy. This project demonstrates the critical role of AI in assisting early diagnosis and supporting clinical decision-making.

Mastered the essentials of relational database management. The course focused on writing structured queries to retrieve and filter complex data.

Explored the core principles of predictive modeling and algorithmic training. This module covered the end-to-end pipeline of building AI models, providing the technical basis for automating workflows and analyzing patterns in complex data.

A professional development workshop on crafting compelling narratives for graduate applications. Teaches students how to effectively articulate their technical achievements and align them with their long-term career goals.

An introduction to the computational tools used to analyze biological data. This project bridged biology and code, focusing on how software is used to map genetic sequences and accelerate drug discovery processes.