knowledge representation

Knowledge-based methods in life sciences

Robert Hoehndorf, Associate Professor, Computer Science

Mar 3, 10:00 - 11:30

B9 L2 H2 R2325

Computer science bioinformatics knowledge representation

In my research I aim to understand how formalized knowledge bases can be used to systematically structure and integrate biological knowledge, and how to utilize these formalized knowledge bases as background knowledge to improve scientific discovery in biology and biomedicine. To achieve these aims, I develop methods for representing, integrating, and analyzing data and knowledge with the specific aim to make the combination of data and formalized knowledge accessible to data analytics and machine learning in bioinformatics. Biomedicine, and life sciences in general, are an ideal domain for knowledge-driven data analysis methods due to the large number of formal knowledge bases that have been developed to capture the broad, diverse, and heterogeneous data and knowledge.

Robert Hoehndorf

Associate Professor, Computer Science

artificial intelligence bioinformatics biomedical data knowledge representation Neuro-Symbolic AI neuro-symbolic methods

Robert Hoehndorf is an Associate Professor of Computer Science at KAUST. His research focuses on bioinformatics, knowledge representation and reasoning, Semantic Web technologies, and neuro-symbolic methods.