rage against the machine learning
personal website of ryan r. curtin
objective

Understand an algorithm. Make it faster.


education

Ph.D. in Electrical and Computer Engineering
Georgia Institute of Technology, Atlanta, GA
Advisors: Dr. David V. Anderson, Dr. Alexander G. Gray, Dr. Charles L. Isbell, Jr.
completed August 2015

Master of Science in Electrical and Computer Engineering
Georgia Institute of Technology, Atlanta, GA
received May 2009

Bachelor of Science with Highest Honors in Electrical Engineering
Georgia Institute of Technology, Atlanta, GA
received May 2008

publications

  1. ``gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation''. C. Sanderson, R.R. Curtin. Submitted to The Journal of Open Source Software.
  2. ``An open source C++ implementation of multi-threaded Gaussian Mixture Models, k-means and expectation maximisation.''. C. Sanderson, R.R. Curtin. Submitted to The 11th International Conference on Signal Processing and Communication Systems (ICSPCS 2017).
  3. ``Designing and building the mlpack open-source machine learning library.''. R.R. Curtin, M. Edel. Submitted to The Fourth International Conference of PUST (ICOPUST 2017).
  4. ``pfsuper: simulation-based prognostics to monitor and predict sparse time series''. J. Echauz, A.B. Gardner, R.R. Curtin, N. Vasiloglou, G.J. Vachtsevanos. Submitted to Annual Conference of the Prognostics and Health Management Society 2017 (PHM '17), 2017.
  5. ``Exploiting the structure of furthest neighbor search for fast approximate results''. Submitted to Information Systems, 2017.
  6. ``Detecting adversarial samples from artifacts''. R. Feinman, R.R. Curtin, S. Shintre, A.B. Gardner. arXiv preprint arXiv:1703.00410, 2017.
  7. ``A dual-tree algorithm for fast k-means clustering with large k'', R.R. Curtin. Accepted to SIAM Data Mining 2017.
  8. ``Armadillo: a template-based C++ library for linear algebra''. C. Sanderson, R.R. Curtin. Journal of Open Source Software, vol. 1:26, pp. 1-2, 2016.
  9. ``Fast approximate furthest neighbors with data-dependent candidate selection''. R.R. Curtin, A.B. Gardner. In Similarity Search and Applications 2016 (SISAP 2016)., p. 221-235, 2016.
  10. ``Improving dual-tree algorithms''. Ph.D. thesis, Georgia Institute of Technology, 2015.
  11. ``Faster dual-tree traversal for nearest neighbor search''. R.R. Curtin. In Similarity Search and Applications, p. 77-89, 2015.
  12. ``Single-tree GMM training''. R.R. Curtin. Technical report GT-CSE-2015-01, Georgia Institute of Technology, School of Computational Science and Engineering, 2015.
  13. ``Collaborative filtering via matrix decomposition in mlpack''. S. Agrawal, R.R. Curtin, S. Ghaisas, M.R. Gupta. In Workshop on Machine Learning Open Source Software 2015, 2015.
  14. ``Plug-and-play runtime analysis for dual-tree algorithms''. R.R. Curtin, D. Lee, W.B. March, P. Ram. The Journal of Machine Learning Research, vol. 16, p. 3269-3297, 2015.
  15. ``An automatic benchmarking system''. M. Edel, A. Soni, R.R. Curtin. In NIPS 2014 Workshop on Software Engineering for Machine Learning, 2014.
  16. ``Classifying broiler chicken condition using audio data''. R.R. Curtin, W. Daley, D.V. Anderson. GlobalSIP 2014 Symposium on Signal Processing Applications Related to Animal Environments, 2014.
  17. ``Dual-tree fast exact max-kernel search''. R.R. Curtin, P. Ram. Statistical Analysis and Data Mining, vol. 7, issue 4, p. 229-253, 2014.
  18. ``Tree-independent dual-tree algorithms''. R.R. Curtin, W.B. March, P. Ram, D.V. Anderson, A.G. Gray, C.L. Isbell, Jr. In Proceedings of The 30th International Conference on Machine Learning (ICML '13), Atlanta, Georgia, 2013.
  19. ``mlpack: a scalable C++ machine learning library''. R.R. Curtin, J.R. Cline, N.P. Slagle, W.B. March, P. Ram, N.A. Mehta, A.G. Gray. In The Journal of Machine Learning Research (JMLR), vol. 14, p. 801-805, 2013.
  20. ``Fast exact max-kernel search''. R.R. Curtin, P. Ram, A.G. Gray. In SIAM International Conference on Data Mining (SDM '13), p. 1-9, Austin, Texas, 2013. Nominated for Best Paper Award.
  21. ``mlpack: a scalable C++ machine learning library''. R.R. Curtin, J.R. Cline, N.P. Slagle, M.L. Amidon, A.G. Gray. In NIPS 2011 Workshop on Big Learning, Granada, Spain, 2011.
  22. ``Learning distances to improve phoneme classification''. R.R. Curtin, N. Vasiloglou, D.V. Anderson. In Proceedings of the 2011 IEEE International Workshop on Machine Learning in Signal Processing (MLSP 2011), Beijing, China, 2011.

professional experience

Symantec Corporation, Atlanta, GA
Center for Advanced Machine Learning
Fall 2015 - present
Principal Research Scientist

My responsibilities at Symantec fall into roughly three categories:


Georgia Institute of Technology, Atlanta, GA
Fall 2009 - Fall 2015
Graduate Research Assistant

At various times I worked for these four labs:



Google, Inc., Mountain View, CA
Summer 2010
Software Engineering Intern


Georgia Tech Research Institute, Atlanta, GA
Food Processing Technology Division
Fall 2009 - Spring 2010
Graduate Research Assistant


Georgia Tech Research Institute, Atlanta, GA
ELSYS Lab
Spring 2009 - Fall 2009
Graduate Research Assistant


Georgia Institute of Technology, Atlanta, GA
School of Electrical and Computer Engineering
Fall 2008
Graduate Teaching Assistant


Nexidia, Inc., Buckhead, GA
Summer 2007
Research Intern


skills


miscellany


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