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johndpope/README.md

Hi there πŸ‘‹

I'm a Full Stack Engineer & Solution Architect with 20+ years of experience in mobile development, AI/ML, and cloud solutions.

πŸ”­ Current Focus

  • Full Stack Development
  • AI/ML Solutions
  • Cloud Architecture
  • Mobile Development (iOS/React Native)

πŸ› οΈ Tech Stack

Languages & Frameworks

Python Swift TypeScript React Vue.js

AI/ML

  • πŸ€– PyTorch | TensorFlow
  • 🧠 NLP & Transformers
  • πŸ‘οΈ Computer Vision
  • ⚑ Generative AI

Cloud & DevOps

AWS Docker Kubernetes

🌟 Featured Projects

  • πŸŽ₯ Video Streaming Platform (WWE) World Wrestling Entertainment - Conneticut USA
  • πŸ“± Social Media Platform with AR (8secondz)
  • πŸš— Ride-Hailing System (Karhoo)
  • πŸ€– AI-Powered Solutions

Recent Projects πŸš€

AI & Computer Vision Research

A recreation of Microsoft's groundbreaking motion synthesis technology

  • Implemented neural motion fields for human motion synthesis
  • Built using PyTorch and CUDA optimizations
  • Focus on performance optimization and memory efficiency

Reverse engineering study of "MegaPortraits: One-shot Megapixel Neural Head Avatars"

  • High-resolution neural head avatar generation
  • Implemented novel architecture for one-shot learning
  • Utilized Claude AI for code analysis and optimization
  • Tech stack: Python, PyTorch, CUDA

Implementation study of VASA (Visual Affective Style Transfer) architecture

  • Audio-driven facial animation synthesis
  • Emotion-preserving style transfer
  • Large-scale model training infrastructure
  • Tech stack: Python, PyTorch, Audio processing libraries

MLOps & Infrastructure

Enterprise-grade MLOps toolkit for A100 GPU clusters

  • Infrastructure as Code
    • Terraform modules for GCP Vertex AI
    • Automated cluster provisioning
    • GPU quota management
  • CI/CD Pipeline
    • Docker containerization
    • Automated deployment workflows
    • Resource optimization
  • Monitoring & Scaling
    • Custom metrics collection
    • Auto-scaling policies
    • Cost optimization

ML-powered cryptocurrency trading strategy generator

  • Real-time market data processing
  • Multiple ML models (Random Forest, LSTM, Transformer)
  • Backtesting framework
  • Risk management system
  • Tech stack: Python, TensorFlow, scikit-learn, pandas

Technical Highlights

  • Advanced computer vision implementations
  • Large-scale distributed systems
  • MLOps and infrastructure automation
  • Performance optimization for GPU clusters
  • Research-to-production pipeline development

πŸ“ˆ GitHub Stats

Your GitHub stats

🌍 Find me around the web

LinkedIn Portfolio

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  1. IMF IMF Public

    Implicit Motion Function - (unofficial) Microsoft recreation

    Python 13 1

  2. MegaPortrait-hack MegaPortrait-hack Public

    Using Claude Opus to reverse engineer code from MegaPortraits: One-shot Megapixel Neural Head Avatars

    Python 77 8

  3. VASA-1-hack VASA-1-hack Public

    Using Claude Sonnet 3.5 to forward (reverse) engineer code from VASA white paper - WIP - (this is for La Raza 🎷)

    Python 223 27

  4. Emote-hack Emote-hack Public

    Emote Portrait Alive - using ai to reverse engineer code from white paper. (abandoned)

    Python 170 9

  5. CryptoCurrencyTrader CryptoCurrencyTrader Public

    A machine learning program in python to generate cryptocurrency trading strategies using machine learning. Sklearn and Tensorflow.

    Python 81 119

  6. vertex-jumpstart vertex-jumpstart Public

    helpers to build / deploy / docker -> dispatch work jobs to A100 clusters.

    Shell 1