I'm an M.S. in Computer Science candidate at the University of Southern California, graduating in May 2027. I build backend systems, cloud applications, and distributed software.
- Completed a Summer 2026 Software Engineering internship at Tech-Management Workshop Co., Ltd., where I developed, secured, tested, and deployed a government-system module using .NET 8, ASP.NET Core MVC, Entity Framework Core, and SQL Server.
- Built the signal-processing and data-preparation pipeline for research accepted by IEEE Transactions on Human-Machine Systems.
- Seeking 2027 new-graduate software engineering roles in the U.S., especially backend, cloud, platform, and distributed systems.
- Languages: C#, C++, Python, JavaScript, SQL
- Backend and Web: .NET 8, ASP.NET Core MVC, Entity Framework Core, Node.js, Express, Flask, Vue.js, REST APIs
- Cloud and Data: Google Cloud Run, Docker, SQL Server, relational database design
- Systems and ML: Git, Linux, OpenGL, GLSL, NumPy, PyTorch, TensorFlow
Node.js · Express · Docker · Google Cloud Run
Built and deployed a cloud application that aggregates the Met Museum, Harvard Art Museums, and Wikipedia APIs, with server-side pagination, interactive maps, artwork details, related works, and persistent favorites.
ASP.NET Core Web API · Entity Framework Core · SQL Server · Vue 3
Building a full-stack task platform with layered services, RESTful APIs, pagination, filtering, sorting, database migrations, and indexed queries. Authentication, automated testing, containerization, and cloud deployment are in progress.
C++ · OpenGL · GLSL
Implemented a custom OBJ/MTL parser, VAO/VBO rendering pipeline, MVP transformations, texture mapping, and multi-light Phong-style shading.
Vue.js · REST APIs
Led a four-developer frontend team and implemented asynchronous submission tracking and API contracts for a distributed code-evaluation platform.
Accepted for publication in IEEE Transactions on Human-Machine Systems
“Noninvasive Portable System With Dual Near-Infrared Light Technology for Monitoring Uric Acid Concentration”
Contributed the PPG signal-processing and model-ready data pipeline, including Bessel filtering, signal-quality screening, feature extraction, and leave-one-subject-out cross-validation.