I design and build interfaces for accessibility, sign language research, and human-centered AI. From React Native apps to computer vision tools.
See selected work →Course projects, research prototypes, and shipped product across mobile, design, and conversational AI.
A React Native app that lets people look up unfamiliar signs by visual parameters like handshape, palm orientation, and body location, instead of typing English words they don't yet know. Built with Deaf native signers, ASL learners, and interpreters on a four-person team (Jen, Dria, Arjun, Daniel).
An iOS map experience that pins curated spots across the Bay Area. Quick filter chips for Food Spot, Live Music, Club, and Bar. Pinned trips you can save. Clean SF Pro typography and Apple Maps as the base layer.
At the Speech and Cognitive Development Lab, I prototype computer vision tools that find signing moments inside longform first-person video. This automates annotation work researchers previously did by hand. Part of an end-to-end multimodal pipeline for sign language acquisition research.
A DSPy agent that recommends films and walks the user through booking a ticket. Item-item collaborative filtering generates personalized picks; structured tool calls handle scheduling, pricing, and booking; a multi-step dialogue layer holds memory across the conversation.
Twice-weekly frontend instruction for 20 Title I high school students.
Taught 20 Title I high school students twice a week in HTML, CSS, and the basics of client-side web architecture. Built hands-on coding exercises and project scaffolds so concepts landed through practice, and ran 1:1 office hours for debugging support. Wrote slides, handouts, and code walkthroughs used across multiple sections, iterated on student feedback.
