DC CAP Innovation Hub — Responsible AI
Live Enterprise AI Governance Framework
I designed DC CAP's enterprise AI Governance Framework and ran the 60-day pilot that introduced it to nine staff across three units, with all materials public at dccapinnovation.org. The framework sets a four-tier data-classification standard that exceeds FERPA and federal-grant requirements, it adapts a research-backed fluency model, 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 15 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 its applicants and university partners. In the 2026 cycle it weighed roughly 700 applicants against 13 partner universities. An exhaustive stability audit tested 9,100 candidate pairs with zero blocking pairs, and fairness mechanisms add neighborhood priority and within-school normalization. That cycle produced 140 priority matches and 70 waitlist offers.
Algorithm Design Stable Matching Fairness Mechanisms Applied Research
