Megan Monroe

Megan Monroe is an Associate Teaching Professor in the Department of Computer Science at Tufts University. Her academic journey includes a Ph.D. and M.S. from the University of Maryland and a B.S. from Carnegie Mellon University.

Research Interests: Monroe specializes in Visual Analytics, focusing on Temporal Data Analysis and Computational Thinking. She developed the EventFlow visualization tool used in healthcare and defense sectors. Her work bridges Artificial Intelligence, Computation Theory, and Human-Computer Interaction.

Publications highlight her contributions to Interactive Visualization, Temporal Querying, and Multi-user Environments, with applications in healthcare data and machine learning debugging.

• Scientific Awards:
  • Information is Beautiful Awards (2016)
  • HCIL-Yahoo! Research Award (2013)
  • VAST 2013 Honorable Mention
  • Audience Choice Award at Pitch Dingman Competition (2011)

Monroe’s teaching includes Computation Theory, Machine Structures & Programming, and Teaching Computer Science courses. She previously worked at IBM Research, designing tools for Watson technologies.