USC Information Sciences Institute
I am a Research Scientist in the Center on Knowledge Graphs within the Information Sciences Institute (ISI) at the USC Viterbi School of Engineering. I hold a Ph.D. in Natural Language Processing from the Vrije Universiteit (VU) in Amsterdam. My areas of expertise are knowledge graphs, common sense reasoning, and knowledge extraction.
Talks and Events
2022 Tutorial: Knowledge Graph Toolkit
Our tutorial will be organized as follows. In the first half of the tutorial, we will introduce KGTK’s data format and the wide range of import, curation, transformation, analysis, and export commands, which can be flexibly chained into streaming pipelines through the command line. In the second half, we will show the utility of KGTK in several common and diverse KG use cases. This tutorial will introduce AI researchers and practitioners to effective tools for addressing a wide range of KG creation and exploitation use cases, and inform us on how to bring KGTK closer to its users. KGTK is publicly available under the MIT license
2022 Talk: CSKG: The CommonSense Knowledge Graph
Common sense reasoning is an important aspect of building robust AI systems and is receiving significant attention in the natural language understanding, computer vision, and knowledge graphs communities. At present, a number of valuable commonsense knowledge sources exist, with different foci, strengths and weaknesses. I will present an overview of existing sources of common sense knowledge, including common sense knowledge graphs, lexical resources, and visual commonsense sources. I will discuss how these can be harmonized in a single Commonsense Knowledge Graph (CSKG), organized into high-level dimensions of common sense, and enriched with logical axioms and preconditions. I will discuss our neuro-symbolic models that combine CSKG with neural language models to reason in question answering, natural language inference, and story understanding tasks. I will conclude with a list of remaining fundamental challenges for organizing common sense knowledge and using it in combination with today’s neural techniques.