Thursday July 2, 11am
Professor Daizy Zhe Wang
Title: Archimedes: A Probabilistic Master Knowledge Base System
In this talk, I discuss novel system components and algorithms that we are designing and building at UF to enable a probabilistic master Knowledge Base (KB) system. In the context of the Archimedes project, I will discuss a spectrum of research directions we are exploring at the UF Data Science Research (DSR) group including: query-driven and scalable statistical inference, probabilistic data models, state-parallel and data parallel data analytics framework, multimodal (e.g., text, image) information extraction, and KB schema enrichment. This line of research of supporting analytics over automatically extracted knowledge bases is of high impact for many applications from QA systems, situational awareness to medical informatics. We have received funding from industry as well as federal government including DARPA, EMC, Amazon and Google. Other related projects include DeepDive from Stanford, YAGO from Max Planck Institute, NELL from CMU as well as WikiData/Freebase and Google Knowledge Vault.
Daisy Zhe Wang is an Assistant Professor in the CISE department at the University of Florida. She is the Director of the Data Science Research Lab at UF. She obtained her Ph.D. degree from the EECS Department at the University of California, Berkeley in 2011 and her Bachelor´s degree from the ECE Department at the University of Toronto in 2005. At Berkeley, she was a member of the Database Group and the AMP/RAD Lab. She is particularly interested in bridging scalable data management and processing systems with probabilistic models and statistical methods. She currently pursues research topics such as probabilistic databases, probabilistic knowledge bases, large-scale inference engines, query-driven interactive machine learning, and crowd assisted machine learning. She received Google Faculty Award in 2014. Her research is currently funded by DARPA, Google, Amazon, Pivotal, Greenplum/EMC, Sandia National Labs and Harris Corporation.
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