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Personal profile

Research Interests

Ptofessor Downey's research is focused on natural language processing, machine learning, and artificial intelligence, with a particular interest in the automatic construction of useful knowledge bases from Web text. One goal is to develop techniques and prototypes that extend the state of the art in Web search. Another goal is to theoretically investigate and establish a formal basis for techniques that can learn from unstructured text alone, without hand-labeled data.

More generally, Prof. Downey works on ways to utilize human input more effectively in machine learning. Two directions in this effort involve selecting human input carefully (active learning) or utilizing it in concert with unlabeled data (semi-supervised learning).

Education/Academic qualification

Computer Science and Engineering, PhD, University of Washington

… → 2008

Computer Science and Engineering, MS, University of Washington

… → 2004

Computer Science, Minors in Mathematics and Economics, BS/MS, Case Western Reserve University

… → 2000

Research interests

  • Artificial intelligence
  • Machine learning
  • Natural language processing

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Grants

  • Research Output

    A new evaluation framework for topic modeling algorithms based on synthetic corpora

    Shi, H., Gerlach, M., Diersen, I., Downey, D. & Amaral, L. A. N., Jan 1 2020.

    Research output: Contribution to conferencePaper

  • Estimating marginal probabilities of n-grams for recurrent neural language models

    Noraset, T., Downey, D. & Bing, L., Jan 1 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Riloff, E., Chiang, D., Hockenmaier, J. & Tsujii, J. (eds.). Association for Computational Linguistics, p. 2930-2935 6 p. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 2 Scopus citations

    Using large corpus N-gram statistics to improve recurrent neural language models

    Yang, Y., Wang, J. P. & Downey, D., Jan 1 2019, Long and Short Papers. Association for Computational Linguistics (ACL), p. 3268-3273 6 p. (NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference; vol. 1).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Construction of the literature graph in semantic scholar

    Ammar, W., Groeneveld, D., Bhagavatula, C., Beltagy, I., Crawford, M., Downey, D., Dunkelberger, J., Elgohary, A., Feldman, S., Ha, V., Kinney, R., Kohlmeier, S., Lo, K., Murray, T., Ooi, H. H., Peters, M., Power, J., Skjonsberg, S., Wang, L. L., Wilhelm, C. & 3 others, Yuan, Z., Van Zuylen, M. & Etzioni, O., Jan 1 2018, Industry Papers. Association for Computational Linguistics (ACL), p. 84-91 8 p. (NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference; vol. 3).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 21 Scopus citations

    Controlling global statistics in recurrent neural network text generation

    Noraset, T., Demeter, D. & Downey, D. C., Jan 1 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI Press, p. 5333-5341 9 p. (32nd AAAI Conference on Artificial Intelligence, AAAI 2018).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 1 Scopus citations