Algorithms & Randomness Center (ARC)
ThinkTankTalk
B. Aditya Prakash (Georgia Tech)
Monday, November 16, 2020
Virtual via Bluejeans - 11:00 am
Title: Networks and Propagation for Fun, Profit and Social Good
Abstract: Given a population network and current infection data of a contagious disease like flu, how to effectively allocate vaccines? What if the infection patterns change? How to fill-in missing infections, automatically? Can we guess if a user is sick from her tweet? Answering all these questions involves the study of aggregated ‘propagation (cascade)’-based dynamics over complex connectivity patterns. As diverse as these problems sound, they can all be approached using modern tools of network science and dynamics. Networks are powerful tools for modeling processes and situations of interest in real-life. They are ubiquitous, from online social networks, gene-regulatory networks, to router graphs. Dynamical processes on networks are also widespread across several 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 will focus largely on public health applications and present some of our past and ongoing work on theoretical results on behavior of fundamental models and scalable algorithms for various associated tasks e.g. immunizing, detecting and reverse engineering epidemics.
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