Hendrika Maclean
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Also affiliated: University of Arkansas System (2026)
Research Areas
Biography and Research Information
OverviewAI-generated summary
Hendrika Maclean's research focuses on the application of large language models (LLMs) and artificial intelligence (AI) to data governance and management. Her work investigates policy-aware generative AI for secure and auditable data access, as well as coordinated multi-agent architectures for automated data governance using LLMs. Maclean has also explored novel approaches using LLMs for multilingual customer record linkage and cross-lingual entity resolution. Additionally, her research includes evaluating the semantic and syntactic understanding capabilities of LLMs within the context of payroll systems. Her publication record includes four papers, with her most recent work appearing in 2026. Her scholarship metrics include an h-index of 1 and a total of 7 citations.
Metrics
- h-index: 1
- Publications: 4
- Citations: 7
Selected Publications
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A Coordinated Multi-agent Architecture for Automated Data Governance Using Large Language Models (2026)
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Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution (2026)
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Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems (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
- A Coordinated Multi-agent Architecture for Automated Data Governance Using Large Language Models
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- A Coordinated Multi-agent Architecture for Automated Data Governance Using Large Language Models
- Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems
- Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution
- Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems
- A Coordinated Multi-agent Architecture for Automated Data Governance Using Large Language Models
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- Policy-Aware Generative AI for Safe, Auditable Data Access Governance
- Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems
- Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems
- Multilingual Customer Record Linkage: A Novel Approach Using LLMs for Cross-Lingual Entity Resolution
- A Coordinated Multi-agent Architecture for Automated Data Governance Using Large Language Models
- A Coordinated Multi-agent Architecture for Automated Data Governance Using Large Language Models