Skip to content
View GabrielJung0727's full-sized avatar
😓
A little overloaded at the moment. Thanks for your understanding.
😓
A little overloaded at the moment. Thanks for your understanding.

Organizations

@Discord-Joy-Support @Kyungbok-ai-study @CampusON @biz-doublej

Block or report GabrielJung0727

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
GabrielJung0727/README.md

Gabriel Jung - AI Full-Stack Engineer

About Me

I am a university student and an AI full-stack software engineer focused on building practical AI-powered applications.

My portfolio website showcases my projects, experiments, and development work:

🌐 Portfolio:
https://gabrieljung0727.github.io/

My work spans AI model experimentation, full-stack development, and production deployment, with a particular interest in Natural Language Processing (NLP) and applied AI systems.

What I Do

  • AI Application Development
    Building services powered by modern AI models and APIs.

  • Full-Stack Engineering
    Designing and developing complete web services including frontend, backend, and infrastructure.

  • AI Model Integration
    Integrating machine learning models into real-world applications and optimizing them for production.

  • End-to-End Product Development
    From idea → prototype → deployed service.

Portfolio

All major projects, experiments, and development work are available on my portfolio site:

👉 https://gabrieljung0727.github.io/

The portfolio includes:

  • Personal AI experiments
  • Web service projects
  • Client work and research-related development
  • Full-stack systems and infrastructure setups

Workflow

My typical development workflow:

  1. Prototype Phase
    Rapid experimentation using AI APIs and quick service prototypes.

  2. Model Integration Phase
    Implementing or fine-tuning models using frameworks such as Hugging Face.

  3. Production Phase
    Deploying scalable services and optimizing performance.

Summary

I focus on building end-to-end AI-powered services, combining AI model integration, full-stack development, and deployment infrastructure to deliver practical applications.

Pinned Loading

  1. Kyungbok-ai-study/.github Kyungbok-ai-study/.github Public

  2. biz-doublej/university biz-doublej/university Public

    TypeScript