معرفی
Manfred Jaeger is a Professor in the Department of Computer Science at Aalborg University's Faculty of Engineering and Science. With an extensive publication record spanning over three decades from 1993 to 2025, he has established himself as a leading researcher in statistical relational learning and probabilistic reasoning. His collaborative work extends across multiple institutions, with frequent co-authorship with researchers from Aalborg University including Kim G. Larsen, Thomas D. Nielsen, and others.
Professor Jaeger's research primarily focuses on the intersection of artificial intelligence, machine learning, and probabilistic modeling. His work centers on developing methods for learning and reasoning with relational and graph-structured data, with particular emphasis on Graph Neural Networks, Bayesian Networks, and Statistical Relational Learning. His contributions span both theoretical foundations and practical applications, addressing challenges in representation learning, knowledge extraction, and uncertainty modeling in complex relational domains.
Analysis of his recent publications (2020-2025) reveals a strong trend toward integrating neural approaches with traditional probabilistic reasoning frameworks. His work increasingly focuses on explainable AI within graph learning contexts, meta-path learning for heterogeneous networks, and bridging theoretical guarantees with practical implementations. Jaeger has made significant contributions to understanding projectivity in statistical relational models and developing algorithms for learning from coarse or incomplete data.
Professor Jaeger has maintained a highly productive research trajectory, with numerous publications in top-tier AI venues including JMLR, Artificial Intelligence journal, UAI, IJCAI, and ECML/PKDD. He has developed influential frameworks for relational Bayesian networks and statistical relational learning, with applications spanning knowledge graph reasoning, network analysis, and decision-making under uncertainty.
