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. The themes of this year's symposium are domain-informed models and learning and fundamental learning limits of 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.

The symposium will take place on Tuesday, August 15th - Wednesday, August 16th, 2023 at the MIT Endicott House.


Symposium Highlights

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

  • Physics-, Knowledge-Informed Models and Learning
  • Social Dynamics and Influences
  • Explainable, Transparent Graph Learning
  • Adversarial Graph Analysis and Learning
  • Analysis of Anomalous, Covert, and Hidden Communities
  • Inference Under Noise and Uncertainty
  • Modeling, Prediction, Control and Optimization
  • Recent Advances in Machine Learning on Graphs
  • Graph Learning for Combinatorial Optimization
  • Various Applications Including Misinformation on Social Media, Cyber Defense,
    Bio/Material Design, Climate Change, Resilient Infrastructures and Systems


Symposium Organizers


Anu Myne | MIT Lincoln Laboratory

Dennis Ross | MIT Lincoln Laboratory

Rajmonda Caceres | MIT Lincoln Laboratory


Technical Co-Chairs

Benjamin Miller | MIT Lincoln Laboratory

Edoardo Airoldi | Temple & Harvard University

Edward Kao | MIT Lincoln Laboratory

Jason Matterer | MIT Lincoln Laboratory

Lin Li | MIT Lincoln Laboratory

Technical Committee

Alexander Volfovsky | Duke University

Ali Pinar | Sandia National Laboratories

Christopher Long | U.S. Department of Defense

David Martinez | MIT Lincoln Laboratory

Heidi Perry | MIT Lincoln Laboratory

Johan Ugander | Stanford University

Jordan Crouser | Smith College

Robert Bond | MIT Lincoln Laboratory

Steven Smith | MIT Lincoln Laboratory