I spend my days at the edges — where data meets intuition, research meets building, and technology meets the deeply human act of learning and connection.
Currently an Education Data Science student at Stanford (MS ’26), I draw from HCI, learning sciences, data, and applied AI to build tools that center human judgment, creativity, and care alongside technical capability.
code , I…My work spans the full arc of AI x education, vertically from K–12 to higher ed to the workplace, and horizontally from product to data to policy and community engagement.
Lately, this has meant deploying an end-to-end teacher–AI collaborative feedback platform at the Stanford Lytics Lab, shaping curriculum-grounded AI product discovery at Goodnotes Education, and building data annotation pipelines for LLM evaluation at TeachFX.
I also run bootcamps, workshops, and communities of practice on responsible AI in education at Learnest ↗, Minds Studio ↗ and Good Future Foundation ↗.
I seek an intentional breadth that leads toward depth, rather than dilution. Multiple lenses that allow me to engage with AI transformation through its friction, beyond its promise.
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Whether you're working on responsible AI, learning science, or just want to think out loud about education and technology.