Profiles

Robert Hoehndorf is an Associate Professor of Computer Science at King Abdullah University of Science and Technology (KAUST), where he is the principal investigator of the Bio-Ontology Research Group (BORG).

Before joining the University in the fall of 2014, Professor Hoehndorf obtained his Ph.D. in Computer Science from the University of Leipzig, Germany, in 2009. Post-graduation, he spent several years in the U.K. as a research fellow and a research associate at Aberystwyth University and the University of Cambridge, respectively. He was also a postdoctoral fellow at the European Bioinformatics Institute, U.K.

Professor Hoehndorf’s main academic interests are knowledge representation, neuro-symbolic methods and their application in life sciences. He develops knowledge-based methods for analyzing large, complex and heterogeneous biological datasets and applies them to understanding genotype-phenotype relations.

His group developed the DeepGO methods for protein function prediction, neuro-symbolic methods applicable to Semantic Web ontologies and knowledge graphs, and several approaches to represent, reason over, and predict genotype-phenotype relations.

I am a PhD student of computer science in Bio-Ontology Research Group under the supervision of Professor Robert Hoehndorf interested in mathematical and programming applications to natural sciences. In 2023 I graduated from Moscow State University, Faculty of Mechanics and Mathematics, Department of Mathematical Logic and Theory of Algorithms. In 2021 I acquired a second degree in the field of algorithmic bioinformatics. From 2020 to 2023 I worked as a research assistant in Ivannikov Institute for System Programming of the Russian Academy of Sciences; my research there was related to ECG signal classification with deep learning techniques and ECG delineation.

My current research interests are related to the development of ontology embedding methods and knowledge-enhanced learning with application to natural sciences.