Hello!
I'm Matt Zhu, a software engineer focused on building impactful web and mobile applications that solve real-world problems.
Get in touch mz223@duke.edu
I'm currently a Software Engineer at Vertice AI, a fast-growing fintech startup that delivers consumable AI to drive member growth for community financial institutions. Previously, I graduated from Duke University with an MS degree in Computer Science and Economics in 2024.
Utilizing my dual background in fintech, I have touched on every aspect of software engineering, spanning data engineering, analytics, AI/ML, database management, backend, and frontend development. Since day one, I have delivered innovative and impactful features that help scale our solution and drive business success.
Outside of work, I always love exploring new experiences — from discovering new travel destinations and trying different ice cream flavors from Ben & Jerry's, to keeping up with the latest tech trends or AI products. You'll also find me capturing stunning sunset photos or cheering for Duke basketball teams!
- Python
- JavaScript
- Java
- C/C++/C#
- Swift
- Dart
- SQL
- HTML
- CSS
- Django
- Flask
- Express.js
- React.js
- Vue.js
- Bootstrap
- UIKit
- SwiftUI
- Node.js
- REST APIs
- MongoDB
- MySQL
- SQLite
- PostgreSQL
- Firebase
- Figma
- Docker
- Kubernetes
- CI/CD
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Microsoft Azure
connects to MediaBeacon, Duke's digital asset system. Users can view, download, and upload files, with changes syncing to the MediaBeacon server. This mobile interface enhances digital asset management efficiency.
enables professors to manage groups and posts, while both professors and students can create posts and answer questions, all authenticated via Keycloak. Built with Node.js, Express.js, Vue.js, and MongoDB, it features E2E testing in Playwright and a CI/CD pipeline in GitLab.
Engineered an iOS directory app in Swift, with a multi-view interface for efficient directory management, integrated robust HTTP/REST services for efficient handling of extensive JSON data and multiple CRUD operations
Implemented Dijkstra’s and A* algorithms and obstacle detection algorithms in C++ to find the shortest path, utilizing data structures such as Priority Queue and HashMap in the C++ STL for optimized graph traversal.
* Performed exploratory data analysis (EDA) and feature engineering to identify and handle imbalanced data issues, * Applied multiple balanced ML algorithms (e.g., Balanced Random Forest) to predict employee attrition rate, ensembled with Voting Classifier, * Produced a robust F1 score of 75%, ranking top 25% in Kaggle Competition