Prospective students

If you are a prospective PhD student hoping to work with me, you do not need to email me, as PhD admissions are made not by me but by a departmental committee. The committee will be looking for signs of research potential, where the strongest candidates will have a publication in a natural language processing workshop, conference, or journal such as those on the ACL Anthology. If you have such a publication or otherwise believe you would be a competitive applicant, you may directly apply to the INFO PhD program and list me as the professor you want to work with on the application form. You may also apply to the CS PhD program, though such applications would only come to me if faculty in CS are not interested in advising you.

If you are an undergraduate or masters student, are already at the University of Arizona, are interested in a one-semester directed research, and have taken ISTA 457/INFO 557 (Neural Networks) and/or ISTA 439/INFO 539 (Statistical Natural Language Processing), please email me your experience and interests.

Current students

Graduated students

  • Yiyun Zhao, Ph.D., Linguistics, University of Arizona, 2022
    Thesis: How to probe linguistic knowledge and bias
  • Dongfang Xu, Ph.D., Information, University of Arizona, 2021
    Thesis: Neural Network Algorithms for Ontology Informed Information Extraction
  • Vikas Yadav, Ph.D., Information, University of Arizona, 2020
    Thesis: Evidence Retrieval for Explainable Question Answering
  • Farig Sadeque, Ph.D., Information, University of Arizona, 2019
    Thesis: User behavior in social media: engagement, incivility, and depression
  • John Osborne, Ph.D., Computer and Information Sciences, University of Alabama at Birmingham, 2016
    Thesis: Machine Learning of Composite Concepts and the Alleviation of The Content Completeness Problem in Text Mention Normalization
  • Upendra Sapkota, Ph.D., Computer and Information Sciences, University of Alabama at Birmingham, 2015
    Thesis: Domain adaptation for authorship attribution