Ron Daniel is a founder and AI research leader with over two decades of experience in information description, metadata standards, and applying NLP and machine learning to scientific, technical, and medical information. He led Elsevier Labs for nearly a decade, producing patents, open-source releases, and research that bridge large language models with fact retrieval, verification, and domain-specific reasoning. A co-editor of the original Dublin Core metadata specification and contributor to multiple W3C and IETF standards, he brings rare depth in taxonomy design, linked data, and metadata governance. Now running AI4Science.com, he consults on specializing LLMs for STM users, emphasizing modular systems that augment LLMs with world modeling and introspective verification. His background spans hands-on R&D, standards architecture, and high-level strategy—reflecting both academic rigor (PhD in Electrical Engineering) and practical product-facing experience. An understated strength is his long-standing ability to translate metadata and taxonomy work from 1990s standards into modern AI-driven knowledge systems.
11 years of coding experience
17 years of employment as a software developer
Putnam City High School
Doctor of Philosophy (Ph.D.) Electrical Engineering, Doctor of Philosophy (Ph.D.) Electrical Engineering at Oklahoma State University
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