Research & deep dives
My work on NoSQL data models and the carbon cost of data systems, plus deep dives on model drift, AI governance and the papers I'm reading.
DaMoOpsDaMoOps: NoSQL Model Lifecycle and Sustainable Data ArchitectureA practical framework for evaluating NoSQL design choices across lifecycle risk, cost, latency, and carbon impact in ML systems.model driftModel Drift, AI Governance, and Time-Money-Carbon Trade-offsConnecting production drift monitoring with AI governance and sustainability metrics to prioritize interventions that are both compliant and efficient.EU AI ActEU AI Act: An Operational Playbook for ML TeamsA practical implementation blueprint that maps EU AI Act expectations to day-to-day ML engineering workflows, controls, and release gates.Data EngineeringThe Future of Database Design: Automating Sustainable Data Architecture with DaMoOpAn exploration of how modern data engineering is shifting from intuition-based architecture to automated, quantifiable data model optimization. This article dives into the DaMoOp framework and the critical need to balance performance, financial cost, and environmental impact in big data systems.