"I treat investing like building a distributed system: build for fault tolerance, cut risk decisively when things break, and scale through automation."
I spent 14 years debugging large-scale systems in Silicon Valley. Now, I apply that same discipline to capital allocation.
Before starting Miyama Capital, I was a Senior Staff Engineer at Synopsys, building fault-tolerant systems and data pipelines. In parallel, I’ve been investing my own capital across US, Taiwan, and Japan markets for over 16 years—starting as a side project and gradually evolving into my main focus.
My philosophy is simple: Fault Tolerance.
In engineering, you assume components will fail, so you build redundancy. In investing, I assume I will be wrong, so I build portfolios that can survive mistakes while capturing asymmetric upside.
I am currently building a cross-border investment setup connecting the US, Taiwan, and Japan. I’m always happy to connect with fellow engineers, researchers, and investors who care about using data and AI to make better decisions.
Designed scalable fault injection tooling and data pipelines (Python, Redis) to test software behavior under failure. This experience heavily influenced my "fault-tolerant" investing philosophy.
Developed and maintained a PDML (UPF) parser in C++, achieving ~5× performance improvement through massive codebase refactoring.
Built automation and verification tools for chip manufacturing using Python, C/C++ and C# for high-volume production testing.