Tim Weninger, University of Notre Dame
November 20, 2015
Searle 240A

Abstract: In this talk we present current and ongoing work about how humans create networks of information and navigate those networks in the pursuit of knowledge. First, we will describe a mathematically principled approach that learns the inherent rules that generate any network. With these rules, we can predict the next, most probable, evolution of any network. By applying this model to the most recent knowledge graph, we are able to make broad predictions about what the knowledge graph will look like in the future.

Greg Shakhnarovich, Toyota Technological Institute
November 19, 2015
Social Science Research (SSR) Building 302

Abstract: In this didactic workshop, Professor Shakhnarovich will introduce social scientists to the increasingly powerful and prevalent use of graphical models to model the (social) world. Such models include topic models, used to analyze text, and conditional random fields, used to model peer and spatial effects in locations like organizations and networks. Historically, these systems have been practically impossible to study, but advances in the field of computer vision have made parameter estimation for even large systems possible.

Anshu Dubey, Argonne
November 12, 2015
Searle 240A

Speaker: Anshu Dubey, Computer Scientist, Mathematics and Computer Science Division, Argonne National Laboratory

Host:  Ian Foster

Cristian Danescu-Niculescu-Mizil, Cornell University
November 05, 2015
Social Science Research (SSR) Building 401

Language and Social Dynamics in Online Communities
Cristian Danescu-Niculescu-Mizil, Assistant Professor in the Department of Information Science, Cornell University

Abstract: More and more of life is now manifested online, and many of the digital traces that are left by human activity are in natural-language format.  In this talk I will show how exploiting these resources under a computational framework can bring a new understanding of online social dynamics;  I will be discussing two of my efforts in this direction.

Center for Data Science and Public Policy Team
November 04, 2015
Searle 240

Applying Data Science!

Join us for a monthly discussion series organized by The Center for Data Science & Public Policy, bringing together faculty, researchers, and students from across the university interested in applying new and emerging data science methods and tools to problems they're tackling. The goal is to start discussions around applied data science and create collaborations.

Who's invited: Anyone interested in learning or sharing how data science can help make an impact in their disciplines and research areas.