Friday, November 30 2018
10:00am - 11:00am
Pettit Microelectronics Building
For more information:

Anna Stroup

Add To My Calendar
CSE Seminar, "Leveraging Propagation for Data Mining: From Influenza to Critical Infrastructures"

Join CSE for a seminar with B. Aditya Prakash, assistant professor in the Computer Science Department at Virginia Tech

Friday, November 30th

"Leveraging Propagation for Data Mining: From Influenza to Critical Infrastructures"

B. Aditya Prakash
Assistant Professor,
Virginia Tech
Pettit Microelectronics Building - 102 A&B  
10 am - 11 am 

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? Can we guess if a user is sick from her tweet? How to find failure 'hotspots' in energy grids? How do we quickly zoom out of a graph? 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 graph mining and machine learning. 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 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 critical nodes, correcting noisy data; and (c) Empirical Studies using social media like Facebook 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 epidemiology and public health, critical infrastructure systems to information dissemination.

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 one book, more than 70 refereed papers in major venues, holds two U.S. patents and has given five tutorials (SDM 2018, SDM 2017, SIGKDD 2016, VLDB 2012 and ECML/PKDD 2012) at leading conferences. His work has also received a best paper award and four best-of-conference selections (ICDM 2017, ASONAM 2013, 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. Tools developed by his group have been in use in many places including ORNL, Walmart and Facebook. He received a Facebook Faculty Gift Award in 2015, the NSF CAREER award in 2018 and was named as one of ‘2017 AI Ten to Watch’ by IEEE Intelligent Systems. He is also an affiliated faculty member at the Discovery Analytics Center at Virginia Tech. Aditya's homepage is at: and Twitter handle is: @badityap.

For scheduling information, please contact Anna Stroup at