Deeper understanding
for a more resilient tomorrow.

I was born in Taiwan and adopted to the Netherlands at the age of two. Curiosity about my roots kept bringing me back, until I decided to move to Taipei permanently, learn Mandarin, and build my future here.

Coming back taught me how strongly context shapes understanding — and why it matters to know where a problem comes from before deciding how to solve it.

What drives me most is helping others. I did voluntary work in secondary school in the Netherlands, and I have been volunteering in Taiwan for more than a year. Along the way I realised that mathematics could be another way to help: first the people around me, and now small and mid-sized businesses that want to understand their operations, explore uncertainty and make better decisions.

Understand first. Build second.

I studied Mathematical Engineering in the Netherlands and spent four years at ASML, working on prototype systems for advanced lithography. Mathematics taught me structured reasoning; high-tech engineering taught me to value precision, collaboration, careful validation, and continuous improvement.

It also taught me the principle at the centre of FeiShe: good technical work is not about the most complicated solution — it is about understanding the problem well enough to choose the right approach.

And I have always wanted to know what lies underneath: not only what happens, but why — and what changes when one part moves.

FeiShe brings together three disciplines, because they answer different parts of the same decision: Data Science learns from evidence, Operations Research structures the choices, and Simulation tests them when conditions change.

They are not a checklist: the problem determines the method. Sometimes the most valuable outcome is simply a clearer definition of the problem.

A model should clarify human judgment, not pretend to eliminate it.

Organizations are people, with knowledge that rarely appears in a dataset. Good analysis respects that knowledge — and a sophisticated solution is still the wrong one if it does not fit the people who use it.

FeiShe is a deliberately small, founder-led practice. You work directly with me, which keeps problem definition, analysis, and delivery closely connected.

Although I am based in Taipei, I work with businesses anywhere in the world, remotely or on site. I work fluently in English and Dutch, and my Mandarin grows every day.

The work is technical. The responsibility is personal.

The aim is not to build the largest consultancy, but a practice that is thoughtful, technically serious, personally accountable and genuinely useful.

The most rewarding moment is not when an algorithm produces an answer, but when the structure of a problem becomes visible: a pattern suddenly makes sense, a trade-off appears, or a simulation reveals a consequence before it happens.

Understand deeply. Model carefully. Decide thoughtfully.