Writing
Essays on causal inference, experimentation, uncertainty, model validation, and decision science.
This section is for essays that translate technical methods into decision-facing judgment.
The writing agenda follows the same pattern as the CV:
- How to decide when offline policy evidence is launch-ready, validation-ready, rejected, or unresolved.
- Why support diagnostics matter in off-policy evaluation.
- How interference changes experiment design in marketplaces, recommendation systems, and member-experience systems.
- How privacy-driven signal loss affects incrementality claims.
- How uncertainty should be calibrated to operational decisions rather than reported as a generic interval.
- How interpretable ML, anomaly detection, and AI-assisted software become more useful when framed as decision systems.
Why causal inference matters for industry
Industry
Decision Science
Causal Inference
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