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I am a distinguished researcher at Google, where I lead work on natural-language understanding. My previous positions include chair of the Computer and Information Science department of the University of Pennsylvania, head of the Machine Learning and Information Retrieval department at AT&T Labs, and research and management positions at SRI International. I received a Ph.D. in Artificial Intelligence from the University of Edinburgh in 1982, and I have over 120 research publications on computational linguistics, machine learning, bioinformatics, speech recognition, and logic programming, as well as several patents.  I was elected AAAI Fellow in 1991 for contributions to computational linguistics and logic programming, and ACM Fellow in 2010 for contributions to machine-learning models of natural language and biological sequences.  I was president of the Association for Computational Linguistics in 1993..

Research Interests

  • Natural language processing
  • Machine learning
  • Bioinformatics
I'm also broadly interested in linguistics, cognitive science, biology, and programming languages, and I've published in or around some of those areas.

Other Interests

  • Skiing
  • Geology


Recent Publications

  1. Reading The Web with Learned Syntactic-Semantic Inference Rules
    N. Lao, A. Subramanya, F. Pereira, and W. W. Cohen
    Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning  1017--1026  (2012)
    http://www.aclweb.org/anthology/D12-1093
  2. Distributed acoustic modeling with back-off n-grams
    C. Chelba, P. Xu, F. Pereira, and T. Richardson
    2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  4129-4132  (2012)
  3. Confidence-Weighted Linear Classification for Text Categorization
    K. Crammer, M. Dredze, and F. Pereira
    Journal of Machine Learning Research  13 1891--1926  (2012)
    http://jmlr.csail.mit.edu/papers/volume13/crammer12a/crammer12a.pdf
  4. Automated gene-model curation using global discriminative learning
    A. Bernal, K. Crammer, and F. Pereira
    Bioinformatics  28 1571--1578  (2012)
    http://www.ncbi.nlm.nih.gov/pubmed/22513996
  5. Markov meets Bayes: technical perspective
    F. Pereira
    Commun. ACM  54 90--90  (2011)
    http://doi.acm.org/10.1145/1897816.1897841
  6. Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models
    S. Singh, A. Subramanya, F. Pereira, and A. McCallum
    Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies  793--803  (2011)
    http://www.aclweb.org/anthology/P11-1080
  7. Posterior Sparsity in Unsupervised Dependency Parsing
    J. Gillenwater, K. Ganchev, J. Graça, F. Pereira, and B. Taskar
    Journal of Machine Learning Research  12 455--490  (2011)
    http://www.jmlr.org/papers/volume12/gillenwater11a/gillenwater11a.pdf

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