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Dynamical Processes on Large Networks
(Seminar/Conference)
B. Aditya Prakash
Department of Computer Science
Carnegie Mellon University
How do contagions spread in population networks? Which group should we market to, for
maximizing product penetration? Will a given YouTube video go viral? Who are the best
people to vaccinate? What happens when two products compete? Any insights on these
problems, involving dynamical processes on networks, promise great scientific as well as
commercial value.
In this talk, we present a multi-pronged attack on such research questions, which includes:
(a) Theoretical results on the tipping-point behavior of fundamental models; (b) Scalable
Algorithms for changing the behavior of these processes, like for immunization, marketing
etc.; and (c) Empirical Studies on tera-bytes of data for developing more realistic
information-diffusion models.
The problems we focus on are central in surprisingly diverse areas: from cyber-security,
epidemiology and public health, viral marketing to spreading of hashtags on Twitter and
propagation of memes on blogs.
B. Aditya Prakash (http://www.cs.cmu.edu/~badityap) is a Ph.D. student in the Computer
Science Department at Carnegie Mellon University. He got his B.Tech (in CS) from the
Indian Institute of Technology (IIT) - Bombay. He has published 14 refereed papers in
major venues and holds two U.S. patents. His interests include Data Mining, Applied
Machine Learning and Databases, with emphasis on large real-world networks and time-
series. Some of the inter-disciplinary questions he investigates deal with identifying the
precise role of networks in diffusion of contagion (like viruses, products, ideas). The
mission of his research is to enable us to understand and eventually influence such
processes for our benefit.
More information...
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