Depth over performance
I want to understand the systems I work on, not merely look fluent in them.
An engineer learning to build intelligence people can inspect and trust.
I care about technical depth, but also about the judgment to choose the right problem and the courage to keep working when the path is unclear.
I study Electrical Engineering in Universitas Indonesia's International Undergraduate Program. My work has moved from analog circuits and embedded systems into data products, forecasting, software, and visual reasoning systems.
I have been admitted to UC Berkeley as a Spring 2027 visiting student in the Berkeley International Study Program, Letters & Science. Long term, I want to build AZUMIE around original work in algorithms, NLP, and intelligent systems grounded in real problems rather than AI for its own sake.
In August 2026, I built MindAssembly as a solo project to make a reasoning graph visible and editable. It crystallized a question running through my work: how can complex systems become more inspectable without becoming less powerful?
I have written online since 2021 and now continue as a contributor to Towards Data Science. Writing, teaching, and leading communities shape how I explain complexity and notice the human system surrounding every technical one.
Ambition with usefulness
The work should be technically serious and matter to someone beyond the screen.
Range with a direction
Hardware, software, teaching, and entrepreneurship are not separate identities. They are how I learned to build whole systems.
PythonMATLABSQLNext.jsTypeScriptForecastingMachine learningEmbedded systemsPower systemsProduct design