DC CAP Innovation Hub — Responsible AI
Live Enterprise AI Governance Framework
I designed and run DC CAP's enterprise AI Governance Framework: a 60-day pilot that puts nine staff across three units through a research-backed fluency model, with all materials public at dccapinnovation.org. It sets a four-tier data-classification standard that exceeds FERPA and federal-grant requirements, and it runs in-house with no outside consultant.
AI Governance Responsible AI Change Management Data Classification
View the framework DC CAP Innovation Hub — Product
Building Career Pathway Intelligence Platform
I'm building the Career Pathway Intelligence Platform, a recommendation engine that will help DC CAP students, counselors, and families compare college-and-career pathways. It synthesizes 19 federal data sources into roughly 400,000 ranked pathways, tested across the data pipeline, the ranking methodology, and the AI layer's defenses against fabricated output. It launches in October 2026.
Full-Stack Product Data Engineering AI Safety Recommendation Systems
DC CAP Analytics — Algorithm Design
Live Scholar Matching Algorithm
I built the empirically validated matching algorithm DC CAP runs each year to allocate scholarship offers among roughly 700 applicants and 13 university partners. An exhaustive stability audit tested 9,100 candidate pairs with zero blocking pairs, and fairness mechanisms add neighborhood priority and within-school normalization. The 2026 cycle produced 140 priority matches and 70 waitlist offers.
Algorithm Design Stable Matching Fairness Mechanisms Applied Research
