You are here: Home → SEAS Directory → Ryan P. Adams
Document Actions

Ryan P. Adams

Faculty
  • Assistant Professor of Computer Science
Ryan P. Adams

Contact Information

Office: Maxwell Dworkin 233
Email: rpa [ AT ] seas [ DOT ] harvard [ DOT ] edu
Office Phone: 617-495-3311
Assistant: Ann Marie King
Office: Maxwell Dworkin 133
Email: aking [ AT ] seas [ DOT ] harvard [ DOT ] edu
Office Phone: 617-496-1447

Recruitment Status

Currently accepting graduate students.

Education

  1. B.S., 2004, Electrical Engineering and Computer Science, MIT
  2. Ph.D., 2009, Physics, University of Cambridge

Research Interests

    • Computer Science
    • Artifical Intelligence and Computational Linguistics
    • Intelligent Systems and Computer Vision
    • Theory of Computation

Profile

In July 2011 Ryan P. Adams was appointed as an Assistant Professor of Computer Science at the Harvard School of Engineering and Applied Sciences. Previously, he was a CIFAR Junior Research Fellow at the University of Toronto.

His research focuses on machine learning and computational statistics, but he is broadly interested in questions related to artificial intelligence, computational neuroscience, machine vision, and Bayesian nonparametrics.

Positions & Employment

University of Toronto, Department of Computer Science

  • 2009-2011: Canadian Institute for Advanced Research Junior Fellow

University of Cambridge, Cavendish Laboratory (Department of Physics)

  • 2004-2009: Ph.D. Candidate, Gates Cambridge Scholar

Massachusetts Institute of Technology, CSAIL

  • 2002-2004: Undergraduate Researcher

Honors

  • Best Paper, Thirteenth International Conference on Artificial Intelligence and Statistics(with Hanna Wallach & Zoubin Ghahramani), 2010
  • Honorable Mention, International Society for Bayesian Analysis Leonard J. Savage Award for Outstanding Dissertation in Bayesian Theory and Methods, 2010
  • Honorable Mention, Best Paper, Twenty-Sixth International Conference on Machine Learning (with Zoubin Ghahramani), 2009
  • Honorable Mention, Best Student Paper, Twenty-Sixth International Conference on Machine Learning (with Iain Murray & David J.C. MacKay), 2009

Selected Publications

Conference Papers

  • Iain Murray, Ryan Prescott Adams, and David J.C. MacKay. 

    Elliptical Slice Sampling. In Proceedings of the 13th International Conference on Artificial Intelligence and Statistics. 2010.abstract | pdf | ps | bibtex | code
  • Ryan Prescott Adams and Zoubin Ghahramani. 

    Archipelago: Nonparametric Bayesian Semi-Supervised Learning. 

    In Proceedings of the 26th International Conference on Machine Learning (ICML 2009). 2009.  Honourable Mention for ICML Best Paper abstract | pdf | ps | bibtex | slides | video
  • Ryan Prescott Adams, Iain Murray and David J.C. MacKay. 

    Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities. In Proceedings of the 26th International Conference on Machine Learning (ICML 2009). 2009. Honourable Mention for ICML Best Student Paper abstract | pdf | ps | bibtex | slides | video
  • Ryan Prescott Adams, Iain Murray and David J.C. MacKay. 

    The Gaussian Process Density Sampler. In Advances in Neural Information Processing Systems 21 (NIPS 2008). 2009. abstract | pdf | ps | bibtex | slides
  • Ryan Prescott Adams and Oliver Stegle. 

    Gaussian Process Product Models for Nonparametric Nonstationarity. In Proceedings of the 25th International Conference on Machine Learning (ICML-2008). 2008. abstract | pdf | ps | bibtex | Oliver's slides | video

Faculty CV

rpa-cv.pdf — PDF document, 60Kb