Agam
Iheanyi-Igwe

CS student at Stanford, passionate about mitigating

algorithmic bias and building impactful software.

Education

B.S. in Computer Science (Expected June 2027)

GPA: 3.99/4.0

Associates Degree in STEM Studies (June 2023)

GPA: 3.89/4.0

Incoming Software Development Intern

Software Development Intern

AMP Intern

Designed and implemented a web app with Node.js, Express.js, MySQL, React, and TailwindCSS, providing Stanford CS students a user-friendly interface for tracking course progress and requirements.
Integrated a BeautifulSoup web-scraping pipeline to extract Stanford course data and descriptions.
Implemented a collaborative filtering algorithm to recommend courses based on similar user academic history.

Developed a multi-repository search algorithm, utilizing OpenAI API, MongoDB, and web scraping to efficiently filter and retrieve relevant datasets from OpenML, Kaggle, and UCI repositories.
Provided ML developers with quick, easy access to diverse training data, promoting fairness by exposing models to broader ranges of data.