I develop and study statistical machine learning systems with applications in human language, biology, and social science. Currently, I am most excited about using these technologies to help people learn languages and make music.

Pretentious 3rd-Person Bio: Burr Settles is a research scientist and software engineer at Duolingo, the award-winning website and mobile app offering free language education for the world. Since 2014, he has spearheaded the Duolingo Test Center initiative. He also runs FAWM.ORG, an annual online songwriting experiment. Previously, he was a postdoc in machine learning at Carnegie Mellon University and earned a PhD in computer sciences from the University of Wisconsin-Madison. His book Active Learning — an introduction to learning algorithms that are adaptive, curious, or exploratory (if you will) — was published by Morgan & Claypool in 2012. He has also co-organized several workshops on the subject at leading international conferences (e.g., ICML, NAACL-HLT). Burr gets around by bike and among other things plays guitar in the pop band delicious pastries. ♣

  • Active Learning Book
    B. Settles
    Morgan & Claypool, 2012
    A short introductory text on active learning, a subfield of machine learning and artificial intelligence. For researchers, graduate students, and engineers working in computer science, statistics, psychology, and related fields.
    publisher's website · Amazon.com · active-learning.net
  • Self-directed Learning Favors Local, Rather Than Global, Uncertainty
    D.B. Markant, B. Settles, and T.M. Gureckis
    Cognitive Science, 2015
    pdf · publisher's website
  • Let's Get Together: The Formation and Success of Online Creative Collaborations
    B. Settles and S. Dow
    Human Factors in Computing Systems (CHI), 2013
    pdf · video · blog post
  • Learning from Human-Generated Lists
    K.S. Jun, X. Zhu, B. Settles, and T.T. Rogers
    International Conference on Machine Learning (ICML), 2013
    pdf · video · blog post
  • Closing the Loop: Fast, Interactive Semi-Supervised Annotation With Queries on Features and Instances
    B. Settles
    Empirical Methods in Natural Language Processing (EMNLP), 2011
    pdf · software
  • Toward an Architecture for Never-Ending Language Learning
    A. Carlson, J. Betteridge, B. Kisiel, B. Settles, E.R. Hruschka Jr. and T.M. Mitchell
    National Conference on Artificial Intelligence (AAAI), 2010
    pdf · supplementary data
  • An Analysis of Active Learning Strategies for Sequence Labeling Tasks
    B. Settles and M. Craven
    Empirical Methods in Natural Language Processing (EMNLP), 2008
  • Multiple-Instance Active Learning
    B. Settles, M. Craven, and S. Ray
    Advances in Neural Information Processing Systems (NIPS), 2008
    pdf · code

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