I am a technical staff member at MIT's Lincoln Lab researching visual analytics for cybersecurity. I am interested in building and evaluating tools that augment human reasoning about complex data and systems. Since joining the Lab, I have focused on application areas in the realm of cybersecurity, where data streams are not only notoriously difficult to correlate and reason about but may conceal adversarial behavior (hiding one's tracks). Recently, I have worked in the areas of human-machine teaming and explainable AI systems (XAI); visual analysis tools for cybersecurity datasets; and decision systems for Software-Defined Network (SDN) management. Other interests include cognitive support, evaluation methods, human-computer interaction techniques, art, and design.

In 2015, I finished my Ph.D at Brown University in computer science under the supervision of David H. Laidlaw. My dissertation focused on novel, human-aligned evaluation methods for visualization systems, with the aim of going beyond basic (and perhaps misleading) performance metrics on benchmark tasks. I received the Sc.M degree from Brown in computer science in 2011. Before coming to Brown, I was a software engineer in New Hampshire. In 2007, I received a BA in computer science from Dartmouth College.


  • Ben Ujcich presented our work on analytics for SDN app vulnerability discovery at NDSS 2020! (Feb '20)
  • Our presentation about visual analytics for identifying Unicode phishing attacks won the Best Presentation at the VizSec symposium at IEEE VIS 2019 (Oct '19)
  • Served on the VAST Challenge 2019 organizing committee. Check out the award-winning solutions at our workshop at IEEE VIS 2019 (Oct '19)
  • MIT Lincoln Lab's Communications Office has written a nice press release about our SDN access-control system, DFI, which recently won a 2018 R&D 100 Award (July '19)

Conference and Journal Papers

Abstracts and Posters

Last updated on:
© 2009-19 Steven R. Gomez