Graph Exploitation Symposium Overview

The symposium brings together leading experts from universities, industry, and government to explore the state of the art and define a future roadmap in network science. This year's symposium will focus on these graph research topics: responsible AI, adversarial and representation learning on graphs. In order to provide an interactive environment and promote strong interaction among the attendees, the event will be limited to a small group of invited attendees.

In light of on-going developments with COVID-19, the symposium will take place virtually on Monday, May 16th - Tuesday May 17th, 2022.


Symposium Highlights

As part of the two-day technical program, topics of interest include:

  • Social Influences,
  • Fair, Unbiased, and Ethical Approaches
  • Adversarial Graph Learning
  • Analysis of Anomalous, Covert, and Hidden Communities 
  • Inference Under Noise and Uncertainty
  • Modeling, Prediction, and Control
  • Recent Advances in Machine Learning on Graphs (e.g., GNNs, Knowledge Graphs)
  • Various Applications Including Bio, Cyber, Materials, Climate, Infrastructure, and Social Domains

Symposium Organizers


Rajmonda Caceres | MIT Lincoln Laboratory

Danelle Shah | MIT Lincoln Laboratory


Technical Co-Chairs

Edoardo Airoldi | Temple & Harvard University

Edward Kao | MIT Lincoln Laboratory

Jason Matterer | MIT Lincoln Laboratory

Lin Li | MIT Lincoln Laboratory

Technical Committee

Nadya Bliss | Arizona State University

Robert Bond | MIT Lincoln Laboratory

Johan Ugander | Stanford University

Jordan Crouser | Smith College

David Martinez | MIT Lincoln Laboratory

Benjamin Miller | MIT Lincoln Laboratory

Alexander Volfovsky | Duke University

Christopher Long | U.S. Department of Defense

Ali Pinar | Sandia National Laboratories

Steven Smith | MIT Lincoln Laboratory

Heidi Perry | MIT Lincoln Laboratory