Research Associate Professor of Computer Science
Education
- 2016, Doctoral Degree, Artificial Intelligence, University of Maryland College Park
- 2005, Master's Degree, Computer Science, Carnegie-Mellon University
- 2004, Bachelor's Degree, Electrical and Computer Engineering, Carnegie-Mellon University
- 2004, Bachelor's Degree, Cognitive Science, Carnegie-Mellon University
- 2004, Bachelor's Degree, Computer Science, Carnegie-Mellon University
Biography
Jay Pujara is a research associate professor at the University of Southern California as well as a principal scientist and director of the Center on Knowledge Graphs at the Information Sciences Institute whose principal areas of research are machine learning, artificial intelligence, and data science. He completed a postdoc at UC Santa Cruz, earned his PhD at the University of Maryland, College Park and received his MS and BS at Carnegie Mellon University. Jay is the author of over a hundred peer-reviewed publications and has received four best paper awards for his work. He is a recognized authority on knowledge graphs, has organized the Automatic Knowledge Base Construction (AKBC) and Statistical Relational AI (StaRAI) workshops, has presented tutorials on knowledge graph construction at AAAI and WSDM, and has had his work featured in AI Magazine. Jay has served as principal investigator on a number of impactful projects, including translating language into logic (DARPA CODORD), developing intelligent knowledge management systems (DARPA KMASS), developing a business-oriented knowledge graph (NSF OKN), and automatically determining the reproducibility of scientific research (DARPA SCORE). Prior to his PhD, Jay spent six years at Yahoo! working on mail spam detection, user trust, and contextual mail experiences, and he has also worked at Google, LinkedIn and Oracle.
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