Simulation Engineer based in Japan

Hi, I'm Daichi.
I build Physics Simulations.

I have always been passionate about 3D graphics, physics, and programming—from experimenting with Blender as a child to working as a CAE simulation engineer today. I specialize in combining high-fidelity simulation with cloud infrastructure.

My Story GitHub

My Story

Experimenting with Blender as a child laid the foundation for my career. Fascinated by 3D graphics, physics, and programming, I went on to study fluid simulation for computer graphics at university. Having my short paper accepted at Eurographics is a milestone I am especially proud of.

As I began thinking about how simulation technology could be applied to real-world products and services, I realized that a strong understanding of infrastructure would be essential. After graduating from university, I joined Rakuten Mobile, where I gained extensive experience building and operating backend systems using Kubernetes and other cloud-native technologies.

Today, I work as a CAE engineer at RICOS. By combining my passion for 3D graphics with expertise in physical simulation, computational physics, and modern cloud infrastructure, I contribute to the development of next-generation simulation environments, including a differentiable finite volume method (FVM) solver based on hierarchical grids.

Technical Stack

CAE / CG Physics

Advanced physics simulation and optimization

Hierarchical Cartesian Grid FVMFluid simulationGPU optimization

Infrastructure / Cloud

Scalable infrastructure and operations automation

KubernetesHelmAnsibleJenkinsDistributed systems design

Languages

PythonC++14Rust (PyO3)CUDAOpenGL

Tools & Software

BlenderHoudiniPyTorchMathematica

Work & Personal Projects

Current Work @ RICOS

OSS & Solver Development

I lead development of an open-source Python library for graph processing of physics simulation data, as well as a Differentiable Hierarchical Grid FVM solver.

PythonFVM

graphlow on GitHub

Rakuten Mobile

Cloud Native Operations

Hands-on cloud infrastructure work: stateful apps on Kubernetes, CI/CD automation with Jenkins, and controlled-downtime updates with Ansible.

NII / Waseda Univ.

Academic Research

Research on memory-efficient GPU fluid simulation. This work was accepted as a Eurographics 2019 short paper. It also received a poster award at Visual Computing 2019.

View Publication