I work at the intersection of mathematical logic, AI verification, and large-scale system design. My core thesis: the settings where AI now makes decisions — cities, governments, autonomous multi-agent systems — need an independent, verifiable layer that checks what the AI produces, the way an auditor checks a company's books.
My background is in mathematical logic and semantic programming — work on Gandy-style fixed-point theorems, the P = L problem, and polynomial-computable representations of formal systems. From there I moved into applied AI infrastructure: trustworthy-AI methods that combine large language models with formal logic, and the ENIGMA Axiom verification engine that puts those methods to work.
Today I advise organizations building high-stakes AI — through IAIC FZCO in Dubai — and I organize conferences (MathAI, SmartCity, IAIC events) and editorial initiatives that convene the research community around trustworthy AI.
P = L, polynomial analogues of Gandy's fixed-point theorem, polynomially-computable representations.
Combining LLMs with formal logic systems; formal + factual checking of model outputs (ENIGMA Axiom).
Virtual cities, digital twins, and autonomous AI societies at city scale.
Task-based cognitive architectures; AI + verifiable records for government efficiency and civic intelligence.
I advise organizations building high-stakes AI — invoiced through IAIC FZCO, Dubai.
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