Managing Consultant & Data Management Architect with 17 years engineering enterprise data at scale. AI researcher, patent holder, and author advancing the hardware-software frontier of intelligent systems.
I'm a Managing Consultant and Data Management Architect with 17 years designing and delivering enterprise data systems for some of the world's most complex organisations. My work lives at the intersection of rigorous data engineering, applied machine learning research, and the emerging frontier of AI infrastructure — where hardware physics begins to define the limits of machine intelligence.
My enterprise practice centres on data migration and transformation at scale — most deeply on the Syniti/ADMM platform. I architect ETL transformation logic, mapping action strategies, zfield enrichment pipelines, crontab-based scheduling, and data governance frameworks for SAP ECC-to-S/4HANA programs across manufacturing, financial services, and retail.
In parallel, I pursue academic AI research. My most significant work is HNSKT — Hierarchical Neuro-Symbolic Knowledge Tracing — a framework fusing transformer-based sequence modelling with inductive logic programming (ILP), hypothesis revision, adversarial deconfounding, and cross-domain transfer learning to model how students learn at causal depth. Currently under review at IJAIED (Elsevier).
My most recent invention — the Neural-Holographic Cache Controller (NHCC), U.S. Patent Application No. 19/656,853 — reimagines KV cache management in LLM inference as a hardware architecture problem, introducing phase-conjugate memory retrieval and holographic encoding to overcome the fundamental bottlenecks behind enterprise AI reliability failures.
From hands-on data engineering to strategic architecture advisory, AI research, and invention — building systems that move, govern, and make sense of enterprise data at scale.
Applied research and engineering projects spanning AI infrastructure hardware, educational AI systems, and enterprise data platforms.
Peer-reviewed research, patent filings, and practitioner publications across AI, machine learning, educational technology, and enterprise data systems.
Writing at the intersection of enterprise data practice, AI research, and the deeper questions of how intelligent systems learn and fail.
Available for advisory engagements on enterprise data migration programs, AI architecture review, research collaboration, and speaking invitations. Whether you're navigating a complex SAP transformation, evaluating AI infrastructure, or exploring knowledge tracing system design — I'd like to talk.