Peter is a Principal Scientist in the Intelligent Systems Lab at PARC. He is working on extracting information from documents and incorporating the information into knowledge bases as well as improving the formalisms underlying large knowledge graphs like Wikidata. Peter's research interests center on representing large-scale knowledge and information, particularly taking large amounts of data and turning it into knowledge. Peter has made long-term contributions to description and ontology logics, particularly the W3C OWL Web Ontology Language. Peter designed and implemented large sections of CLASSIC, a Description Logic-based Knowledge Representation system. He designed and implemented DLP, a heavily-optimized prover for expressive Description Logics and propositional modal logics. He has performed extensive empirical evaluation of DLP and other provers for Description Logics and propositional modal logics. He developed much of OWL and its predecessor DAML+OIL, as well as SWRL, the Semantic Web Rule Language, and contributed to RDF, the W3C language for representing data in the Semantic Web. Peter has authored over 200 papers in peer-reviewed venues. His main publication topics are Description Logics, Ontology Languages, the Semantic Web, and Reasoning. He is an editor of the widely used Description Logic Handbooks. Peter Patel-Schneider received his Ph. D. in Computer Science from the University of Toronto. He worked in the Fairchild Laboratory for Artificial Intelligence Research and Schlumberger Palo Alto Research from 1983 to 1988. Peter then joined the AI Principles Research Department at AT&T Bell Laboratories. From 2012 to 2019 he was a member of the NLU and AI Research Laboratory at Nuance Communications. Peter is a fellow of the Association for the Advancement of Artificial Intelligence.