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 social influences on graphs, COVID pandemics, and machine 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 17th - Tuesday May 18th, 2021.


Symposium Highlights

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

  • Social influences
  • Analysis of anomalous, covert and hidden communities
  • Inference under noise and uncertainty
  • Drug discovery and design
  • Pandemic modeling, prediction and control
  • Recent advancement in machine learning on graphs
  • Novel applications of machine learning on graphs
  • Challenges from various applications including bio, cyber, material and social domains


Symposium Organizers


Rajmonda Caceres / MIT Lincoln Laboratory

William Streilein / 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

Timothy Dasey / MIT Lincoln Laboratory

Benjamin Miller / MIT Lincoln Laboratory

Alexander Volfovsky / Duke University

Christopher Long / U.S. Department of Defense

David Martinez / MIT Lincoln Laboratory

Ali Pinar / Sandia National Laboratories

Steven Smith / MIT Lincoln Laboratory