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Talks & Seminars
Title: Leveraging Propagation for Data Mining: Models, Algorithms and Applications
B. Aditya Prakash, Virginia Tech
Date & Time: December 22, 2016 10:30
Venue: KR Bldg Office Conference Room
Abstract:
Can we guess if a user is sick from her tweet? How do contagions like Ebola and Influenza spread in population networks? How do malware propagate? How do rumors spread on Twitter/Facebook? Which group should we market to for maximizing product penetration? Answering all these big-data questions involves the study of aggregated dynamics over large graphs. Dynamical processes over networks can give rise to fascinating macroscopic behavior, leading to research problems which recur in multiple domains. Understanding such propagation processes will eventually enable us to manipulate them for our benefit e.g., understanding dynamics of epidemic spreading over graphs helps design more robust policies for immunization. In this talk we will focus on leveraging propagation-style processes on large networks to understand, predict and manage behaviors. We present a multi-pronged approach, which includes: (a) Theoretical results on the behavior of fundamental models; (b) Scalable Algorithms based on these processes e.g., immunization, finding 'culprits', correcting noisy data; and (c) Empirical Studies on blogs, social media like Twitter and malware databases like at Symantec. We finally conclude with future research directions. The problems we focus on are central in surprisingly diverse areas: from cyber-security, epidemiology and public health, protest prediction, product marketing to information dissemination.
Speaker Profile:
B. Aditya Prakash is an Assistant Professor in the Computer Science Department at Virginia Tech. He graduated with a Ph.D. from the Computer Science Department at Carnegie Mellon University in 2012, and got his B.Tech (in CS) from the Indian Institute of Technology (IIT) -- Bombay in 2007. He has published more than 50 refereed papers in major venues, holds two U.S. patents and has given two tutorials (VLDB 2012 and ECML/PKDD 2012) at leading conferences. His work has also received a best paper award and two best-of-conference selections (CIKM 2012, ICDM 2012, ICDM 2011) and multiple travel awards. His research interests include Data Mining, Applied Machine Learning and Databases, with emphasis on big-data problems in large real-world networks and time-series. His work has been funded through grants/gifts from the National Science Foundation (NSF), the Department of Energy (DoE), the National Security Agency (NSA), the National Endowment for Humanities (NEH) and from companies like Symantec. He received a Facebook Faculty Gift Award in 2015. He is also an affiliated faculty member at the Discovery Analytics Center at Virginia Tech. Aditya's homepage is at: http://www.cs.vt.edu/~badityap.
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