Expertise
My research focuses on the application of semantic web technologies, ontology engineering, artificial intelligence (AI), and decision intelligence for sustainability governance and circular bioeconomy systems. I develop ontology-driven and neuro-symbolic AI frameworks that integrate heterogeneous environmental, economic, governance, technological, and geospatial datasets to support explainable multicriteria reasoning, inferential classification, and evidence-based decision support.
My current research investigates global sugarcane bioeconomy and lignocellulosic supply chain systems using OWL ontologies, SPARQL querying, Retrieval-Augmented Generation (RAG), and large language models (LLMs) to enable transparent and auditable governance analytics. This work combines semantic reasoning with AI-driven knowledge retrieval to support adaptive decision intelligence for biomass valorisation, sustainability benchmarking, and bioeconomy transition planning.
The research further explores how ontology-grounded AI systems can improve explainability, interoperability, and governance alignment within complex industrial and environmental systems. Current applications include semantic classification of sugarcane bioeconomy systems, inferential PESTLE governance modelling, sustainable biorefinery analytics, and AI-assisted policy evaluation across global bio-based supply chains.