Hamed Babaei Giglou From Language to Structured Knowledge

I'm a PhD candidate in Computer Science at Leibniz University Hannover and a doctoral researcher at TIB – Leibniz Information Centre for Science and Technology, supervised by Prof. Dr. Sören Auer and Dr. Jennifer D'Souza. My research sits where natural language processing meets the Semantic Web: I study how large language models can learn, align, and reason over ontologies and knowledge graphs.

I care about turning research into tools people actually use. As part of the Scientific Knowledge Organization (SciKnowOrg) group, which builds AI systems that turn scientific literature into machine-actionable knowledge, I lead the development of the open-source Python libraries OntoAligner, OntoLearner, and YESciEval. OntoAligner received the Best Resource Paper Award at ESWC 2025. I also co-organize the LLMs4OL Challenge series on LLMs for ontology learning.

What drives me is the gap between how much knowledge exists in text and how little of it machines can actually use. Language models are fluent but loosely grounded; ontologies are precise but slow and costly to build by hand. I want to bring the two together, so that structured knowledge becomes easier to create and maintain, and AI systems become more reliable because of it. I'm also motivated by openness: I believe research is most useful when it ships as reproducible benchmarks and tools that others can build on.