I am an associate professor in the University of Maryland Computer Science Department (tenure home), Institute of Advanced Computer Studies, iSchool, and Language Science Center. Previously, I was an assistant professor at Colorado's Department of Computer Science (tenure granted in 2017). I was a graduate student at Princeton with David Blei.

My research focuses on making machine learning more useful, more interpretable, and able to learn and interact from humans. This helps users sift through decades of documents; discover when individuals lie, reframe, or change the topic in a conversation; or to compete against humans in games that are based in natural language.

• My One-page CV
• My Long (and ugly) CV
• My Google Scholar page

Recent Publications

• Chen Zhao, Chenyan Xiong, Xin Qian, and Jordan Boyd-Graber. Complex Factoid Question Answering with a Free-Text Knowledge Graph. The Web Conference, 2020. [Bibtex]
  
  

  @inproceedings{Zhao:Xiong:Qian:Boyd-Graber-2020,
  	Title = {Complex Factoid Question Answering with a Free-Text Knowledge Graph},
  	Author = {Chen Zhao and Chenyan Xiong and Xin Qian and Jordan Boyd-Graber},
  	Booktitle = {The Web Conference},
  	Year = {2020},
  	Location = {Taipei, Taiwan},
  }
  

• Alison Smith, Varun Kumar, Jordan Boyd-Graber, Kevin Seppi, and Leah Findlater. Digging into User Control: Perceptions of Adherence and Instability in Highly Transparent Interactive Models. Intelligent User Interfaces, 2020. [Bibtex]
  
  

  @inproceedings{Smith:Kumar:Boyd-Graber:Seppi:Findlater-2020,
  	Author = {Alison Smith and Varun Kumar and Jordan Boyd-Graber and Kevin Seppi and Leah Findlater},
  	Booktitle = {Intelligent User Interfaces},
  	Url = {http://umiacs.umd.edu/~jbg//docs/2020_iui_control.pdf}
  	Year = {2020},
  	Title = {Digging into User Control: Perceptions of Adherence and Instability in Highly Transparent Interactive Models},
  }
  

• Alison Smith, Jordan Boyd-Graber, Ron Fan, Melissa Birchfield, Tongshuang Wu, Dan Weld, and Leah Findlater. No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML. Computer-Human Interaction, 2020. [Bibtex]
  
  

  @inproceedings{Smith:Boyd-Graber:Fan:Birchfield:Wu:Weld:Findlater-2020,
  	Author = {Alison Smith and Jordan Boyd-Graber and Ron Fan and Melissa Birchfield and Tongshuang Wu and Dan Weld and Leah Findlater},
  	Booktitle = {Computer-Human Interaction},
  	Year = {2020},
  	Url = {http://umiacs.umd.edu/~jbg//docs/2020_chi_explanation.pdf}
  	Title = {No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML},
  }
  

• Mozhi Zhang, Yoshinari Fujinuma, and Jordan Boyd-Graber. Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification. Association for the Advancement of Artificial Intelligence, 2020. [Bibtex]
  
  

  @inproceedings{Zhang:Fujinuma:Boyd-Graber-2020,
  	Title = {Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification},
  	Author = {Mozhi Zhang and Yoshinari Fujinuma and Jordan Boyd-Graber},
  	Booktitle = {Association for the Advancement of Artificial Intelligence},
  	Year = {2020},
  	Location = {New York, New York},
  	Url = {https://arxiv.org/abs/1812.09617}
  }
  

• Benjamin Börschinger, Jordan Boyd-Graber, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Michelle Chen Huebscher, Wojciech Gajewski, Yannic Kilcher, Rodrigo Nogueira, and Lierni Sestorain Saralegu. Meta Answering for Machine Reading. ArXiv, Preprint. [Bibtex]
  
  

  @article{B\"orschinger:Boyd-Graber:Buck:Bulian:Ciaramita:Huebscher:Gajewski:Kilcher:Nogueira:Saralegu-Preprint,
  	Title = {Meta Answering for Machine Reading},
  	Author = {Benjamin B\"orschinger and Jordan Boyd-Graber and Christian Buck and Jannis Bulian and Massimiliano Ciaramita and Michelle Chen Huebscher and Wojciech Gajewski and Yannic Kilcher and Rodrigo Nogueira and Lierni Sestorain Saralegu},
  	Journal = {ArXiv},
  	Year = {Preprint},
  	Url = {https://arxiv.org/abs/1911.04156}
  }
  

• Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and Jordan Boyd-Graber. Quizbowl: The Case for Incremental Question Answering. ArXiv, Preprint. [Webpage] [Bibtex]
  
  

  @article{Rodriguez:Feng:Iyyer:He:Boyd-Graber-Preprint,
  	Title = {Quizbowl: The Case for Incremental Question Answering},
  	Author = {Pedro Rodriguez and Shi Feng and Mohit Iyyer and He He and Jordan Boyd-Graber},
  	Journal = {ArXiv},
  	Year = {Preprint},
  	Url = {https://arxiv.org/abs/1904.04792}
  }
  

• Jordan Boyd-Graber and Benjamin Börschinger. What Question Answering can Learn from Trivia Nerds. ArXiv, Preprint. [Bibtex]
  
  

  @article{Boyd-Graber:B\"orschinger-Preprint,
  	Title = {What Question Answering can Learn from Trivia Nerds},
  	Author = {Jordan Boyd-Graber and Benjamin B\"orschinger},
  	Year = {Preprint},
  	Volume = {10},
  	Url = {https://arxiv.org/abs/1910.14464}
  	Journal = {ArXiv},
  }