Research

Peer-reviewed work on auditable, governed AI systems.

Original contributions spanning zero-trust LLM agents for healthcare and data-driven urban mobility. Every paper ships with its full text and reproducible artifacts.

MedTrust Agent: A Zero-Trust, Observable LLM Agent Framework for Medical and Pharmaceutical Workflows

NEECON 2026 — International Near East Conference on Electrical & Energy Systems

Dubai, UAE · presented Oct 21, 2026 · Technical Session TS3 (Artificial Intelligence), Fursa Ballroom A

Unifies agentic orchestration, zero-trust IAM, retrieval grounding, governance and observability into one evaluable control plane for regulated medical workflows. 100% of unauthorized/high-risk actions blocked (measured, Wilson 95% CI), 100% citation enforcement on released answers, tamper-evident audit chain — plus an honest negative finding: a content filter alone was defeated by an adaptive attacker in 3 rounds.

Zero-TrustLLM AgentsAI GovernanceHealthcare AI

📄 Paper PDF 🎞️ Conference slides 🔗 Official record 📐 Case study & diagrams

A Data-Driven Framework for Urban Mobility: Real-Time Traffic Analysis in Dubai Using Google Maps API and R

IEEE International Conference Proceedings

IEEE · 2025

A novel, cost-effective framework for real-time traffic monitoring and analysis leveraging the Google Maps API and R to extract high-resolution traffic data for smart-city mobility planning.

Urban MobilityGeospatialRGoogle Maps API

📄 Paper PDF 🔗 Official record

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