USC Viterbi Webinar Series on Digital Technologies for COVID-19

Guest Speakers:
Pedro Szekely – USC
Jay Pujara – USC

Friday, May 1, 2020
Zoom Webinar Link
11am – 12pm


USC Viterbi Webinar Series on Digital Technologies for COVID-19

Please click on the following link to register online: https://usc.zoom.us/webinar/register/WN_SnVYd9ONQgyYeLWiI8qtMA

After registering, you will receive a confirmation email containing information about joining the webinar.


Our third webinar will feature a double-header of talks by researchers from USC Viterbi’s Information Sciences Institute.  The first talk will cover work by Pedro Szekely on a knowledge graph for COVID-19 papers, and the second talk will cover work by Jay Pujara on rapidly responding to COVID-19 using knowledge graphs. 

Please find abstracts for these talks as well as the speaker bios below:

 

Talk 1:A Knowledge Graph Integrating Annotations On 44,000 COVID-19 Scientific Articles

Pedro Szekely

Abstract: The COVID-19 Open Research Dataset (CORD-19), compiled by the Allen Institute for AI is a free resource of over 44,000 scholarly articles, including over 29,000 with full text, about COVID-19 and the coronavirus family of viruses. At the ISI Center On Knowledge Graphs we are working to enrich this corpus with annotations obtained using multiple state of the art information extraction tools, bioinformatics databases, and multiple graph and network analytics. These tools are difficult to run and produce outputs in different formats, making it difficult for COVID-19 researchers to use them. We are building a knowledge graph that integrates the outputs of these tools and databases in a simple data model that we provide in multiple formats (TAB-separated, RDF/SPARQL and Neo4J) to facilitate use of the corpus annotations. Our current release enriches the CORD-19 corpus with gene, chemical, disease and taxonomic information from Wikidata and CTD databases, as well as entity extractions from Professor’s Heng Ji BLENDER lab at UIUC. In the next releases we will also integrate extractions from the Reach project at University of Arizona and others. Healthcare adviser here. Levitra is a member of the class of PDE5 inhibitors, which also includes Viagra or Sildenafil, Sulfoaildenafil, Uprima or apomorphine hydrochloride, as well as Cialis or tadalafil. Viagra is available in 25 mg, 50 mg, and 100 mg tablets. The discovery of its active substance (sildenafil) dates back to 1996, by Pfizer laboratories. Levitra comes in tablets of 5 mg, 10 mg, and 20 mg. Like all the treatments mentioned, it requires a doctor’s prescription.

Bio:  Dr. Pedro Szekely (Ph.D. Carnegie Mellon 1987) is a Principal Scientist and Research Director of the Center on Knowledge Graphs at the USC Information Sciences Institute (ISI), and a Research Associate Professor at the USC Computer Science Department. Dr. Szekely’s research focuses on algorithms and tools for rapid construction of domain-specific knowledge graphs. The tools developed in his group have been used in several DARPA and IARPA projects to construct knowledge graphs in cyber security, causal exploration, hypothesis generation and forecasting of geo-political

events, and has been used by law enforcement agencies to identify victims of human trafficking and to build legal cases against the traffickers. Dr. Szekely teaches a graduate course at USC on Building Knowledge Graphs, and has given tutorials on knowledge graph construction at KDD, ISWC, AAAI and WWW.

 

Talk 2: Rapidly Responding to COVID-19 Using Knowledge Graphs


Jay Pujara

Abstract: Responding to the COVID-19 pandemic has created a need to navigate vast amounts of information and quickly make decisions. I will describe how knowledge graphs, structured repositories capturing interconnected information, can help quickly adapt to new circumstances. To illustrate the value of these techniques, I will describe two active projects in our research group. The first allows experts to sift through thousands of research papers and identify scientific results that are likely to be reproducible. The second helps manufacturers adapt their supply chains to develop health and safety projects. Both projects are the result of analyzing terabytes of data and developing a succinct representation that can help answer questions with rich information.

Bio: Jay Pujara is a research assistant professor of Computer Science at the University of Southern California and a research lead 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. Prior to his PhD, Jay spent six years at Yahoo! working on mail spam detection and user trust, and he has also worked at Google, LinkedIn and Oracle. Jay is the author of over thirty peer-reviewed publications and has received four best paper awards for his work. He is a recognized authority on knowledge graphs, and has organized the Automatic Knowledge Base Construction (AKBC) and Statistical Relational AI (StaRAI) workshops, presented tutorials on knowledge graph construction at AAAI and WSDM, and had his work featured in AI Magazine. For more information, visit https://www.jaypujara.org 

Series co-hosted by:
Craig Knoblock, Executive Director, USC Information Sciences Institute
Bhaskar Krishnamachari, Director, USC Viterbi Center for CPS and IoT