Mobile & AI Engineer

Hi! I am Ryan

Full-stack engineer building production apps with React Native, Swift, computer vision, and privacy-first AI.

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Ryan Yang

Mobile & AI Engineer

01. BIO

Product-Focused Engineer.

I build production-minded mobile products that combine applied AI, native device capabilities, and careful UX. Across HabitForge, Seekr, and TrainTogether, I have shipped work spanning React Native, Swift, Gemini integration, on-device models, LiDAR scanning, spatial search, and privacy-first data flows.

At the University of Toronto, I am strengthening my foundations in algorithms, math, and software design while continuing to ship real products. My volunteer work in tech support and teaching sharpened my communication and collaboration, and I care about building software that is technically rigorous, reliable, and genuinely useful.

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02. WORKS

Featured Projects

HabitForge

React Native Expo TypeScript Swift Clean Architecture

- AI-powered habit tracking with personalized recommendations using Google Gemini AI

- Smart expense management with natural language input ("Bought coffee for $5")

- Native iOS widgets with real-time sync - complete habits and log expenses from the Home Screen

- Gamification system with levels, quests, achievements, streaks, and mini-games

- Intelligent budget tracking with category breakdowns and a financial health score

View on App Store Support

Seekr

Swift ARKit LiDAR RTAB-Map OpenCV PCL SceneKit

- Real-time 3D scanning and reconstruction using RTAB-Map SLAM for mobile spatial mapping

- ARKit + LiDAR fusion for precise spatial reconstruction and loop-closure support

- Hierarchical tagging system (Furniture -> Container -> Item) with 3D coordinates

- Full-text search with location-aware navigation to exact 3D positions

- Internationalization with English and Simplified Chinese support

- Privacy-first local storage with support for large spaces and dense tagging

View on App Store Support

TrainTogether

Swift SwiftUI MediaPipe llama.cpp CoreML HealthKit WidgetKit AVFoundation

- Real-time form analysis using MediaPipe for responsive on-device feedback

- On-device LLM coaching with llama.cpp and local model execution

- Multi-agent coaching flows with context-aware feedback and streaming responses

- More than 32 exercise detection algorithms with custom rep counting and biomechanical logic

- HealthKit and AVFoundation integration for workout syncing and camera-based feedback flows

View on App Store Support

03. ENGINEERING

How I Build

I focus on production-minded mobile products that balance strong UX with applied AI, native device capabilities, and privacy-conscious architecture. Together, these projects show range across cross-platform delivery, native iOS systems, spatial computing, and on-device intelligence.

Mobile Product Engineering

Shipping polished product flows from UI to platform integrations

I build end-to-end app experiences, from interface design and local state to widgets, synchronization, exports, and device-native integrations.

React Native + Expo Swift + SwiftUI WidgetKit HealthKit iCloud sync

AI, ML & Computer Vision

Applying AI where it improves the workflow, not just the marketing

The portfolio mixes cloud-assisted AI, on-device models, and classical vision pipelines depending on the product constraint, latency target, and privacy requirement.

Gemini integration llama.cpp CoreML MediaPipe RTAB-Map + ARKit

Privacy-First Systems

Designing around trust, offline utility, and device constraints

I favor local-first storage, narrow cloud usage, and clear data boundaries so the product remains useful even when privacy, connectivity, or latency matter.

Local-first storage Peer-to-peer sync Private iCloud container On-device inference Offline-capable flows

04. VISUALS

Lens & Light

Full Gallery

05. CONTACT

RyanY153@outlook.com