Portfolio 2025

Nirai Hayakawa

> AI Researcher & Developer

17 years old

Bridging the gap between academic research and practical application. Specializing in Computer Vision, LLMs, and Game AI at CU Boulder.

Status

Available for work

Click to see Slack status

Slack Status

Based in

Miyazaki, Japan 🇯🇵

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Core Stack

Python PyTorch TensorFlow OpenCV Rust TypeScript Astro AWS Docker Git

About Me

Hello! I'm a researcher and developer with extensive experience in AI/ML applications for esports and gaming. I have a demonstrated ability to develop innovative solutions that bridge academic research with practical applications.

Currently, I am conducting research on LLM-driven algorithm optimization frameworks for NP-hard problems and have published research on computer vision and video analysis.

Tech Stack

Python C++ Rust Typescript Swift Deep Learning Machine Learning LLMs Computer Vision Unity Unreal Engine AWS GCP Next.js Astro

Experience

Software Engineer Intern

Present

Not A Hotel Inc.

  • Researching and implementing standard methodologies for AI agent evaluation frameworks.
  • Focusing on LLM as a Judge approach for automated AI system assessment.
  • Designing comprehensive evaluation frameworks for AI agents across multiple domains.

R&D Product Developer Intern

2025/08/01-2025/10/31

CLINKS Corporation

  • Independently developed a comprehensive Proof of Concept (PoC) from initial design to implementation.
  • Developed a Speech-to-Speech LLM Agent system.
  • The demo is scheduled for release in December. I look forward to seeing it in action.

Software Developer (Part-time)

2024/04/01-2025/06/31

Bird Fab Studio

  • Developed an automated texture packaging system using Python and LLM integration.
  • Reduced review failures to nearly zero and implemented automatic proofreading/translation.
  • Created a comprehensive documentation system for the texture platform.
  • Developed additional internal tools, including native applications.

Featured Projects

VALORANT Round Outcome Prediction

Collaborated with NAIST to develop a transformer-based deep learning approach for predicting round outcomes using minimap video analysis. Achieved 80.55% accuracy and constructed a dataset from 1,376 tournament videos.

Python Deep Learning Computer Vision TimeSformer OpenCV

Publications

Ongoing Research

Ongoing Projects

Certifications

AWS Cloud Solutions Architect Professional
Google Cloud Cybersecurity Professional
Google Data Analytics Specialization
DeepLearning.ai Deep Learning Specialization
IBM Generative AI Engineering Professional
Microsoft AI & ML Engineering Professional
IPA Applied Information Technology Engineer

Achievements

Ready to collaborate?

I'm currently open for freelance projects and full-time opportunities. Let's build something amazing together.