Kaichi Irie (入江海地)

日本語

System Optimization Laboratory, Applied Mathematics and Physics Course, Graduate School of Informatics, Kyoto University

I'm a second-year master's student at the Graduate School of Informatics, Kyoto University, researching continuous optimization — particularly black-box optimization. I also contribute to Optuna, an open-source hyperparameter optimization framework.

Research

  1. Optuna Constrained Tree-Structured Parzen Estimator Is a Joint Density Generalization of c-TPE

    S. Watanabe, K. IriearXiv preprint (arXiv:2606.09889), 2026

  2. Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization

    K. Irie, S. Watanabe, M. Onishi5th Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE), 2025

Open Source

Internships

  1. Recruit Co., Ltd. Software Engineer Intern

    Oct 2025 – Nov 2025Tokyo

  2. Preferred Networks Software Engineer Intern

    Aug 2025 – Sep 2025Tokyo

    Worked on speeding up the GPSampler in Optuna.

  3. Nikkei Software Engineer Intern

    Mar 2025 – Aug 2025

    Designed and built a preprocessing pipeline for LLM training data on Amazon SageMaker.

  4. AbemaTV (ABEMA) Data Scientist Intern

    Sep 2023

Projects

Education

  1. Graduate School of Informatics, Kyoto University M.S. in Informatics

    Apr 2025 – Mar 2027 (expected)GPA 3.93 / 4.3

    System Optimization Laboratory, Applied Mathematics and Physics Course(opens in a new tab)

  2. Faculty of Economics, Kyoto University B.A. in Economics

    Apr 2021 – Mar 2025GPA 3.66 / 4.3

Skills

Languages
Python, Go, Julia, C++
Focus
Continuous optimization, black-box optimization, Bayesian optimization, hyperparameter optimization
Tools
Optuna, PyTorch, Amazon SageMaker, Git, Docker

Languages

Japanese
Native
English
Business level

Certifications