Put AI to Work
April 15-18, 2019
New York, NY
Lise Getoor

Lise Getoor
Professor, University of California, Santa Cruz

Website

Lise Getoor is a professor in the Computer Science Department at the University of California, Santa Cruz, and director of the UCSC Data Science Research Center. Her research areas include machine learning, data integration, and reasoning under uncertainty, with an emphasis on graph and network data. Previously, she was a professor in the Computer Science Department at the University of Maryland, College Park. Lise has over 250 publications and extensive experience with machine learning and probabilistic modeling methods for graph and network data. She is a fellow of the Association for Artificial Intelligence and an elected board member of the International Machine Learning Society; she serves on the board of the Computing Research Association (CRA) and was cochair for ICML 2011. Lise is a recipient of an NSF Career Award and 12 best paper and best student paper awards. She holds a PhD from Stanford University, an MS from UC Berkeley, and a BS from UC Santa Barbara.

Sessions

11:05am–11:45am Wednesday, April 17, 2019
The unreasonable effectiveness of structure
Models and Methods
 Location: Grand Ballroom West
Secondary topics:  Models and Methods
Lise Getoor (University of California, Santa Cruz)
Average rating: ****.
(4.50, 4 ratings)
Much of today's data is noisy, incomplete, heterogeneous in nature, and interlinked in a myriad of complex ways. Lise Getoor discusses AI methods that are able to exploit both the inherent uncertainty and the innate structure in a domain. Along the way, Lise explores the benefit of utilizing structure—and the inherent risk of ignoring structure. Read more.