Selected work

Projects at the edge of models and people.

Two close looks at how I frame problems, build systems, and learn from the limits of data.

Ongoing research · 2026

Designing technology around how people learn

I’m contributing to an ongoing computing education research project exploring how human-centered technology can support mathematical learning. Further details are being withheld while the work is under development.

The question

Educational tools should support understanding without replacing a learner’s own reasoning. The project examines that broad design challenge in collaboration with educators and researchers.

The approach

My contribution includes prototyping and human-centered design. Specific mechanisms, study materials, and findings are intentionally omitted while the research is ongoing.

The work continues to shape how I think about responsible educational technology: usefulness depends on whether a system supports thoughtful action.

EECS 486 capstone · 2026

A more honest view of social media risk

A machine-learning and information-retrieval project exploring self-reported productivity loss, with an interactive experience that compares a user with similar profiles.

The question

Survey data about attention and productivity is noisy, subjective, and often internally inconsistent. A polished score can hide that uncertainty rather than clarify it.

The approach

I evaluated an XGBoost model on a public dataset, then studied where data quality constrained performance. The companion web application uses vector embeddings to find similar profiles and presents comparisons instead of treating one prediction as a universal verdict.

The strongest outcome was not a single metric. It was a product direction that surfaces context and uncertainty so users can interpret a model’s result responsibly.