Nathan Tran

Hayward, California

• Won Best Multimodal Use of Groq for developing an AI-powered Browser Agent that autonomously navigates websites and completes tasks via voice commands, utilizing PyGame for rendering the Browser Assistant 3D Model and Groq for processing the website's DOM.

Santa Clara, California

• lmk is a real-time incident tracking platform that empowers communities to report and monitor local safety concerns through an interactive map interface with AI-powered classification and alert systems. The project combines Next.js, Mapbox, and a sophisticated AI pipeline featuring Classifier, Warning, Summarizer, and Aggregator agents to process incident reports and deliver relevant, actionable safety information to users based on severity and proximity.

Stanford, California

• Won Best Use of Amazon AWS and Best Integration of AI prizes for Dreamscapes, a VR sandbox enabling voice-commanded 3D model generation. Created an AI pipeline using FLUX.1-schelle and TripoSR models to convert text to 3D meshes in ~30 seconds, while implementing Redis vector search for asset caching and AWS S3 for model storage and delivery.

San Francisco, California

• Collaborated with Snap Spectacles to develop NutriLens, an AR application that provides nutritional information and recipe suggestions based on photos taken through smart glasses, built using TypeScript and JavaScript while integrating USDA nutrition data, AR technology, and AI-powered image recognition for food identification and macro tracking.