A practitioner-researcher
Working at the intersection of AI, decision-making, technology, and institutions. The trajectory bends from a language and cross-cultural background into information systems, financial systems, government digital systems, AI/Data, teaching, and now research.
Humanities → Information Systems → Financial Systems
→ Digital Government → AI / Data → Product
→ Human-AI Decision Making → AI Governance / Philosophy of Technology
Practice
From N-PORT regulatory reporting at State Street to three provincial big-data platforms under "Digital Yunnan," from on-chain trading systems at NX Lab to AI grading systems in development — practice has always been about making decision-grade data legible and trustworthy.
Research
The doctoral programme traces a single recursive structure: human–AI reliance → explanation → control → governance. Four themes organise the work: Human–AI Decision Making, AI Governance, Sociotechnical Systems, and Philosophy of Technology.
Methods
Computational social science meets philosophical analysis. Product management meets field research. The methods are hybrid because the questions sit between disciplines — between a philosopher's question and a product manager's edge case.
Direction
Applying to doctoral programs in Philosophy of Technology / Science & Technology Studies (STS). The goal is not to leave practice behind, but to give it a longer arc — from closing one edge case at a time to understanding the grammar that connects them all.
