• Digital-Health-Conference-2020

Invited SpeakersProfile Details

Prof. Robert Hoehndorf
Prof. Robert Hoehndorf Robert Hoehndorf is an Assistant Professor in Computer Science at King Abdullah University of Science and Technology in Thuwal.


Robert Hoehndorf is an Assistant Professor in Computer Science at King Abdullah University of Science and Technology (KAUST) in Thuwal. Prior to joining KAUST, Robert had research positions at Aberystwyth University, the University of Cambridge, the European Bioinformatics Institute, and the Max Planck Institute for Evolutionary Anthropology. His research focuses on the applications of knowledge-based algorithms in biology and biomedicine. Robert is an associate editor for the Journal of Biomedical Semantics, BMC Bioinformatics, Applied Ontology, PLoS ONE, and editorial board member of the journal Data Science. He published over 100 research papers in journals and international conferences.

All sessions by Prof. Robert Hoehndorf

  • Day 1Monday, January 20th
  • Day 3Wednesday, January 22nd
3:45 pm

PANEL DISCUSSION - (Moderator - Takashi Gojobori) (Co-Moderator - Fadwa Attiga)

Building 20 15:45 - 16:45 Details

Session 5 : AI & Computational Resources (Chair Dr. Katsuhiko Mineta)
11:10 am

Logic, Logic, Logic, and Medicine

Knowledge representation is a sub-field of AI which studies
how to represent information about a domain so that is can be utilized for a wide range of tasks. In particular, the life sciences have created a large amount of formalized knowledge bases. In my talk, I will show how to use information in formalized knowledge bases as background knowledge in statistical analyses and machine learning.

I will discuss an algorithm to construct a map from formal theories into vector spaces that preserve the model-theoretic semantics of the theories while enabling new operations within the vector space. Combining methods from knowledge representations with machine learning can be used to generate explanations and exploit background knowledge, which is particularly important in knowledge-intensive disciplines such as biology and medicine.

Building 19, Hall 1 11:10 - 11:35 Details