Creative Technologist

Hi! I am Ryan

A Full-Stack Developer building the next generation of web and mobile applications that shape real life.

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Ryan Yang

Full-Stack Dev

01. BIO

Passionate Developer.

I'm a developer focused on building intelligent, user-centred software that blends AI, mobile development, and modern systems engineering. I've released multiple iOS apps, including HabitForge, an AI-powered habit and finance tracker, and Seekr, a LiDAR-based 3D scanning and organization tool—projects that reflect my full-stack skills and comfort with technologies like SLAM, point-cloud processing, and React Native.

At the University of Toronto, I maintain a high GPA while deepening my foundations in algorithms, math, and software design. My volunteer work in tech support and teaching strengthened my communication and teamwork abilities, and I'm driven to build reliable, impactful products that genuinely help people.

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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 home screen

• Gamification system: level up character, daily/weekly quests, achievement badges, streaks, mini-games

• Intelligent budget tracking with real-time monitoring, category breakdowns, and financial health score

View on App Store Support

Seekr

Swift ARKit LiDAR RTAB-Map OpenCV PCL SceneKit

• Real-time 3D scanning & reconstruction using RTAB-Map SLAM algorithm for millimeter-accurate mapping

• ARKit + LiDAR fusion for precise spatial reconstruction with appearance-based loop closure detection

• Intelligent hierarchical tagging system (Furniture → Container → Item) with 3D coordinates (SIMD3<Float>)

• Full-text search with high-performance Swift algorithms and color-coded navigation to exact 3D locations

• Internationalization: English and Simplified Chinese with runtime language switching

• Privacy-first: local storage only, supports large-scale scenarios (thousands of tags, hundreds of spaces)

View on App Store Support

TrainTogether

Swift SwiftUI MediaPipe llama.cpp CoreML HealthKit WidgetKit AVFoundation

• Engineered real-time form analysis engine using MediaPipe achieving steady 60fps inference on mobile devices

• Implemented on-device LLM inference using llama.cpp with Qwen3.0 0.6B Q8 for AI coaching with streaming token generation

• Built multi-agent AI coaching system with context-aware feedback, thinking token separation, and web search integration

• Developed 32+ exercise detection algorithms (push-ups, squats, deadlifts, planks, burpees, etc.) with custom rep counting and biomechanical load calculation

• Integrated HealthKit and AVFoundation for workout syncing, background delivery, and AR-like spatial feedback overlays

View on App Store Support

04. VISUALS

Lens & Light

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05. CONTACT

RyanY153@outlook.com