cv
My curriculum vitae, keeping brief for anonymity.
Basics
| Nickname | masuwaka |
| Label | An engineer |
| masuwaka@masuwaka.net | |
| Url | https://masuwaka.net/ |
| Summary | A Japanese AI researcher, data scientist, and system administrator of AI computing clusters. |
Work
-
2024.10 - Present System administrator of AI computing clusters
System administration of large AI computing clusters (w/ hundreds of nVidia GPUs).
- LDAP
- Ansible
- Zabbix
- CUDA
- Linux (Ubuntu)
-
2017.10 - Present AI research engineer / data scientist
Research and development of state-of-the-art AI technologies. I am also working on data mining from big data.
- Neural Network
- Bayesian Optimization
- Tensorflow (Keras)
- PyTorch
- Optuna
- Pandas
- Python
- Linux (Ubuntu)
-
2016.04 - 2017.09 ECC (Error Correction Codes) engineer
Engaged in research on energy-efficient, reliable ECCs. I also developed Python environment for ECC analysis.
- LDPC Codes
- BCH Codes
- C/C++
- Python
- Linux (RHEL)
Education
-
2011.04 - 2016.03 Yokohama, Japan
Skills
| Mathematics | |
| Probability | |
| Statistics | |
| Coding Theory | |
| Communication Theory | |
| Signal Processing | |
| Information Theory |
| Programming | |
| C/C++ | |
| Python | |
| Shell script (bash/zsh) | |
| PyTorch | |
| Numpy | |
| Pandas | |
| Optuna | |
| gPyTorch | |
| BoTorch |
| System Management | |
| LDAP | |
| Ansible | |
| Zabbix | |
| Linux |
Languages
| Japanese | |
| Native speaker |
| English | |
| Conversational |
Interests
| Mathematics | |
| Optimization Theory | |
| Manifold Theory | |
| Quantum Information Theory | |
| Quantum Computation |
| Programming | |
| Rust | |
| Polars | |
| cuDF | |
| cuPy | |
| SIMD | |
| Omniverse |
Projects
- 2025.07 - Present
A fast and highly interpretable Python library for manipulating multivariate Gaussian distributions
Manipulations of Gaussian distributions are sometimes too cumbersome and troublesome especially when the distributions are multivariate. In this project, I am developing a Python library that enables calculation of product, quotient, marginal, and conditional distributions of multivariate Gaussian distribution more easily and with higher interpretability.
- Multivariate Gaussian Distributions