Jordan Boyd-Graber

Jordan Boyd-Graber

Jordan Boyd-Graber

Associate Professor
2118C Hornbake Library
(301) 405-7414


  • Making machine learning more useful, more interpretable, and able to learn from humans.

Current Research Interests

  • Human-Computer Interaction
  • Data Science
  • Machine Learning


  • PhD, Computer Science, Princeton University, 2010
  • MA, Computer Science, Princeton University, 2007
  • BS, Computer Science / History, California Institute of Technology, 2004


  • NSF Career Award, Quora Top Writer, Best Paper Awards NAACL & CoNLL, Best Demonstration Award NIPS, Karen Spärk Jones Award, Richter Undergrad Research Fellowship, Caltech Jorgensen Scholarship, AAAI Research Award.

Joint Appointment

  • 25% College of Information Studies
  • 25% College of Computer, Mathematical, & Natural Sciences
  • 25% Maryland Language Science Center
  • 25% Institute for Advanced Computer Studies (UMIACS)

RI: Medium: Collaborative Research: Closing the User-Model Loop for Understanding Topics in Large Document Collections

Principal Investigator: Jordan Boyd-Graber

This project brings together machine learning researchers and human-computer interaction researchers to build effective environments for information exploration.

Adaptive Heads-up Displays for Simultaneous Interpretation

Associated Research Centers:
Principal Investigator: Hal Duame
Investigator: Jordan Boyd-Graber