Knowledge Engineering

Knowledge engineering focuses on building and maintaining systems that create and utilize knowledge, bridging the gap between human expertise and artificial intelligence. Current research emphasizes integrating large language models (LLMs) with traditional knowledge representation techniques, such as knowledge graphs and Bayesian networks, to improve knowledge acquisition, refinement, and reasoning capabilities. This interdisciplinary field is crucial for developing robust and reliable AI systems across diverse domains, from industrial applications and healthcare to scientific discovery and environmental monitoring, by enabling the efficient representation and utilization of complex, real-world knowledge.