About Me
I'm a senior at UCLA pursuing dual degrees in Computer Science and Mathematics of Computation, with a strong foundation in software engineering, database systems, and machine learning.
My experience spans from building internal tooling at Garmin for aviation database management to developing full-stack web applications and iOS apps. I thrive on solving complex problems and creating software that makes a real impact.
When I'm not coding, you'll find me on the golf course, rock climbing, or playing tennis. I'm always eager to take on new challenges and collaborate on innovative projects.
UCLA 2026
CS & Math of Computation
2 Internships
Garmin & Terracon
Full Stack
Web, Mobile & ML
Experience
Software Engineering Intern
Garmin
Olathe, KS
- ▹ Designed and built an internal Python application with a Tkinter UI to input, retrieve, and manage aviation database data using SQL Server
- ▹ Implemented JSON export and SQL Server integration to enable real-time data input, retrieval, and editing
- ▹ Built robust internal tools in C++, Python, and C# to support aviation database packaging and verification
- ▹ Designed a SQLite diff engine to track changes in data files and generate detailed reports
Software Development Intern
Terracon
Olathe, KS
- ▹ Developed a console application in C# to integrate SQL Server logging tables with Elastic, improving search speeds by up to 3x
- ▹ Transitioned a major desktop application from Oracle SQL to SQL Server, doubling database interaction speeds
- ▹ Modified multiple internal applications to run on automated pipelines for frequent data processing
- ▹ Used Visual Basic .NET to maintain and upgrade legacy interfaces
Projects
BruinDigest
Full-stack AI-powered news aggregator that automatically summarizes r/ucla Reddit posts using Gemini AI, enabling UCLA students to stay informed through intelligent content curation and daily news summaries.
- User authentication with JWT
- Real-time commenting system
- PWA for mobile accessibility
- Kubernetes deployment
EchoScribe
iOS app using Swift and Apple's SNClassifier framework to classify common sounds and transcribe speech in real-time, aiding users with hearing impairments.
- 500+ sounds with 95%+ accuracy
- Real-time speech transcription
- Accessible UI design
ViT Semantic Segmentation
Built a Vision Transformer (ViT) encoder for semantic segmentation on the MiniPlaces dataset, training and evaluating across classification tasks.
- Custom ViT architecture
- Semantic segmentation pipeline
- Performance benchmarking
Skills
Languages
Frameworks
Tools
Methods
Education
University of California, Los Angeles
B.S. Computer Science & B.S. Mathematics of Computation
2022 - 2026 | Los Angeles, CA