Hey! I'm
William Zhang...
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ABOUT
I'm currently a student at Northeastern University studying computer science and cognitive psychology. An aspiring software engineer, I am passionate about creating innovative solutions to complex problems.I've been lucky enough to work at NASA, where I achieved a life-long dream of working on a project that pushes forward space and aeronautic exploration. I also worked at Travelers, where I was able to help build an innovative application boosting the overall quality of code in the company. Now, I'm working with the Bureau of Reclamation as an AI engineer intern, working a model for classifying structural damage.Feel free to reach out! I'll probably be climbing, watching a Celtics game, or trying to build something new...EXPERIENCE
JANUARY 2025 - PRESENT
AI Engineer Intern - US Bureau of Reclamation
Developing models to identify structural damage using machine learning. 👨🏻💻
JUNE 2024 - DECEMBER 2024
Software Engineer Intern - Travelers Insurance
Maintained and implemented new features for an application, Engineering Insights, for the Technology Value Stream in Claim using React, MongoDB, and Node along with AWS. Engineering Insights is an application that allows teams to holistically review their application's codebase in terms of security, company-wide standards, and other engineering best practices.
AUGUST 2023 - DECEMBER 2023
Applications Developer Intern - NASA, Langley Research Center
Designed and developed a web application for NASA Langley's Strategic Partnerships Office to manage and track the status of agreements. Collaborated with the Office of Chief Information Officer to ensure the application met NASA security and design standards. Prepared extensive documentation for the basis of future iterations of the application. Allowed for the expedited development of agreements that are crucial to scientific research and development.
PROJECTS
Kanji Radical Match AI
Developed a feedforward neural network capable of learning the relationship between English words and Japanese radicals. Trained model on extensive datasets from sources such as JMDict allowing for accurate predictions of associations. The model was able to predict correct radicals with up to 80% confidence of association.
NBA MVP Classifier
Implemented three machine learning models to predict whether or not a player is worthy of the NBA MVP award. Implemented SVM, KNN, and decision tree models to find the model with highest accuracy based on past NBA seasons. The model was able to accurately predict the MVP winner with 97% accuracy.
willzhang.dev
Personal website build using modern web technologies including but not limited to React, React Three Fiber, and Bootstrap. Coded in Visual Studio Code and eployed with Vercel.