CSIS logoCenter for Secure Information Systems

Securing the World's Cyber Infrastructure

Aerial View of the George Mason Fairfax Campus

CSIS Seminar

Mining and Learning from Graph Processes

Speaker:   Arlei Silva, University of California, Santa Barbara
When:   February 15, 2021, 11:00 am - 12:00 pm
Where:   Zoom


The digital transformation has given rise to a new form of science driven by data. Graphs (or networks) are a powerful framework for the solution of data science problems, especially when the goal is to extract knowledge from and make predictions about the dynamics of complex systems such as those arising from epidemiology, social media, and infrastructure. However, this representation power comes at a cost, as graphs are highly combinatorial structures, leading to challenges in search, optimization, and learning tasks that are relevant to modern real-world applications. In this talk, I will overview my recent work on new algorithms and models for mining and learning from graph data. First, I will show how the interplay between a graph structure and its dynamics can be exploited for pattern mining and inference in networked processes, such as improving the effectiveness of testing during an epidemic. Then, I will focus on machine learning on graphs, where novel deep learning and optimization approaches for predicting graph data, such as traffic forecasting, will be described. As the last topic, I will introduce combinatorial algorithms for optimization on graphs that enable us to attack/defend their core structure, among other applications. I will end by briefly contextualizing my ongoing work as part of a broader research agenda with new related problems that I plan to address in the next few years. Join Zoom Meeting https://gmu.zoom.us/j/91959246582?pwd=SWdTVlhqblBZNHp4NHA2dmYxN2JUUT09 Meeting ID: 919 5924 6582 Passcode: 587177

Speaker Bio

Arlei Silva is a postdoctoral researcher at the University of California, Santa Barbara, where he also completed his Ph.D. Earlier, he received bachelor's and master's degrees from Universidade Federal de Minas Gerais, in Brazil. His research focuses on new algorithms and models for mining and learning from complex datasets, especially graphs. His work has been published at several venues including ICLR, WebConf (previously WWW), SIGKDD, AAAI, IJCAI, VLDB, AAMAS, SDM, ICDM, ICDE, and TKDE. He has also been the chair of the UCSB Graduate Student Workshop on Computing, the president of the UCSB CS Department Graduate Student Council, and a PC member for WebConf, AAAI, SDM, AAMAS, IJCAI, DSAA, and COMAD.