My focus is AI-powered data systems engineering — the design, integration, and evaluation of systems that combine data engineering with AI/LLM capabilities.

This grew out of my work as a researcher and engineer: leading data integration and analytics projects with institutions like UNICAMP (funded by FAPESP), working across sources like Scopus, Dimensions, and PatentScope to turn unstructured research and patent data into structured, analyzable systems, and building backend systems for US/EU clients as a senior engineer at Brick Abode.

I currently serve as Head of the Informatics Engineering Department and Assistant Professor at Arab International University, where I teach and research AI-powered data systems. I'm now building this into structured public education — starting with a free introductory course and a full training path on designing and evaluating AI-powered data systems, launching first in Arabic with English to follow.

I'm particularly interested in the practical, unglamorous parts of this discipline: how systems behave reliably at scale, how to validate what an LLM extracts rather than trust it blindly, and how data pipelines fail and recover in production — not just what's possible in a demo.

I welcome conversations with engineering teams and researchers working on real-world data and AI integration challenges, particularly around system architecture, data pipelines, reliability, and evaluation.