Autonomous AI Agent Benchmarking & Search Systems Engineering

Advancing multi-agent software engineering, deterministic AST compilation, and empirical search optimization standards across modern developer ecosystems.

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Dr. Amara Okafor

Principal Information Retrieval Researcher & Neural Search Specialist

Dr. Amara Okafor is a computer scientist specializing in neural information retrieval, knowledge graph embeddings, and AI search engine ranking algorithms. Her research examines algorithmic citation mechanics, semantic entity modeling, and information gain scoring in modern LLM search engines.

Published Technical Research & System Benchmarks

2026-08-13 • Research Paper

Information Gain Engineering: Aligning Content Architecture with Google's US Patent 11,562,019 B2

A mathematical examination of Google's Information Gain patent, showing how autonomous multi-agent systems structure entity-attribute-value graphs to maximize algorithmic trust and visibility in AI search summaries.

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2026-07-28 • Research Paper

Entity-Attribute-Value (EAV) Modeling for AI Search Engines

How structured knowledge triples improve document understanding in Perplexity, Google SGE, and Bing Copilot.

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2026-07-16 • Research Paper

Algorithmic Information Gain vs. Semantic Content Repetition

Why rehashed AI articles fail to rank and how novel empirical data triggers algorithmic trust.

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2026-07-02 • Research Paper

Knowledge Graph Embeddings in Modern Search Indexing

Bridging vector embeddings with structured ontologies to maximize search engine citability.

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