Shames Al Mandalawi
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
Also affiliated: Arkansas Department of Agriculture (2025–2026)
Unknown Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Shames Al Mandalawi's research focuses on the application of advanced artificial intelligence, particularly large language models (LLMs), to complex data governance and privacy challenges. His recent work investigates policy-aware generative AI for secure and auditable data access, demonstrating a commitment to enhancing data security and compliance. Al Mandalawi has also explored novel approaches to multilingual customer record linkage, utilizing LLMs for cross-lingual entity resolution and structured knowledge extraction from large datasets while preserving privacy. His research contributes to the development of secure architectures for LLM-mediated data governance, addressing the critical need for robust data protection in increasingly data-driven environments. Al Mandalawi collaborates with researchers at the University of Arkansas at Little Rock, including Mert Can Çakmak and John R. Talburt, contributing to a shared body of work in these areas.
Metrics
- h-index: 1
- Publications: 4
- Citations: 2
Selected Publications
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Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution (2026)
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Positive Data Control: A Secure Architecture for LLM-Mediated Data Governance (2026)
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Policy-Aware Generative AI for Safe, Auditable Data Access Governance (2025)
Collaboration Network
Top Collaborators
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- Positive Data Control: A Secure Architecture for LLM-Mediated Data Governance
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- Positive Data Control: A Secure Architecture for LLM-Mediated Data Governance
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- Positive Data Control: A Secure Architecture for LLM-Mediated Data Governance
- Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution
- Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution
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