Rebecca A. Hutchinson
Postdoctoral Fellow
2069 Kelley Engineering Center 
School of Electrical Engineering and Computer Science
Oregon State University
Corvallis, OR 97331

rah AT eecs DOT oregonstate DOT edu

CV in pdf format



Research
My postdoctoral research is at the intersection of machine learning and ecology.  The unifying theme of my current work is incorporating nonparametric methods like boosted regression trees into ecological latent variable models.  Since observations of ecological processes are often imperfect and incomplete, ecologists often use hierarchical latent variable models to specify a model of the true ecological process of interest along with a model relating the observations to that process.  However, ecological processes are also complex, and the need to identify a parametric function of potentially many input variables for use in a hierarchical latent variable model may be overwhelming.  Regression trees avoid the need to define the relationship of the inputs to the model quantities in advance, and they automatically capture nonlinearities and interactions.  Unfortunately, they do not handle latent variables, so they cannot take advantage of the expressiveness of hierarchical models.  My goal is to unite these two approaches, in hopes that ecologists will not have to choose between an ecologically plausible hierarchical model and the ability to deal with many inputs with complex effects.

I am a SEES (Science, Engineering, and Education for Sustainability) Fellow, funded by the National Science Foundation.  I am thrilled to be working with two excellent mentors:  Dr. Thomas G. Dietterich and Dr. Matthew G. Betts.  



Software

We plan to release an R package implementing the methods we are developing.  That package is under development, but check back here for updates!


Education

Ph.D., Computer Science Department, 2009
Carnegie Mellon University, Pittsburgh, PA
Advised by Dr. Tom M. Mitchell


B.S., Computer Science & Engineering, 2002
Bucknell University, Lewisburg, PA



Refereed Publications

"A Latent Variable Model for Discovering Bird Species Commonly Misidentified by Citizen Scientists,"
J. Yu, R.A. Hutchinson, W-K.Wong,
Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI), 2014.

"Species distribution modeling for the people: Unclassified landsat TM imagery predicts bird distributions at fine resolutions in forested landscapes,"
S. Shirley, Z. Yang, R.A. Hutchinson, J. Alexander, K. McGarigal, and M.G. Betts,
Diversity and Distributions, Vol. 19, Issue 7, pp. 855-866.  2013.

"Project and Analysis Design for Broad-Scale Citizen Science,"
W. Hochachka, D. Fink, R.A. Hutchinson, D. Sheldon, W-K. Wong, and S. Kelling,

Trends in Ecology and Evolution
, Vol. 27, Issue 2, pp. 130-137.  2012.

"Incorporating Boosted Regression Trees into Ecological Latent Variable Models,"
R.A. Hutchinson
, L-P. Liu, and T.G. Dietterich,

Proceedings of the Twenty-fifth Conference on Artificial Intelligence
(AAAI), 2011.  

"Modeling Experts and Novices in Citizen Science data for Species Distribution Modeling,"
J. Yu, W-K. Wong, and R.A. Hutchinson,

International Conference on Data Mining
(ICDM), 2010. 

"Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models,"
R.A. Hutchinson
, R.S. Niculescu, T.A. Keller, I. Rustandi, and T.M. Mitchell,

Neuroimage
(2009), doi:10.1016/j.neuroimage.2009.01.025.  (preprint version)

"Hidden Process Models,"
R.A. Hutchinson
, T.M. Mitchell, and I. Rustandi,
International Conference on Machine Learning (ICML), 2006.  

"Learning to Decode Cognitive States from Brain Images," 
T.M. Mitchell, R.A. Hutchinson, R.S. Niculescu, F.Pereira, X. Wang, M. Just, and S. Newman,
Machine Learning
, Vol. 57, Issue 1-2, pp. 145-175.  2004.

"Training fMRI Classifiers to Detect Cognitive States across Multiple Human Subjects ," 
X. Wang, R.A. Hutchinson, and T.M. Mitchell,
Neural Information Processing Systems
(NIPS), 2003.

"Classifying Instantaneous Cognitive States from fMRI Data," 
T.M. Mitchell, R.A. Hutchinson, M. Just, R.S. Niculescu, F. Pereira, and X. Wang,
American Medical Informatics Association Symposium
(AMIA), 2003. (received Best Foundational Paper Award)

"Reducing Boundary Friction Using Translation-Fragment Overlap," 
R. Brown, R.A. Hutchinson, P. Bennett, J.G. Carbonell, and P. Jansen.  
Machine Translation Summit IX.
 2003. 


Other Papers

"Machine Learning for Computational Sustainability,"
T.G. Dietterich, E. Dereszynski, R.A. Hutchinson, and D. Sheldon,
International Conference on Green Computing (IGCC), 2012. 

"Modeling Experts and Novices in Citizen Science data for Species Distribution Modeling,"
J. Yu, W-K. Wong, and R.A. Hutchinson,

OSU EECS Technical Reports
, October 7, 2010.


"Hidden Process Models,"
R.A. Hutchinson
,

Ph.D. Thesis
, CMU Technical Report CMU-CS-09-179.  
December 18, 2009.

"Hidden Process Models,"
R.A. Hutchinson
,
Thesis Proposal, May 26, 2006.


"Hidden Process Models,"
T.M. Mitchell, R.A. Hutchinson, and I. Rustandi. 

CMU Technical Report CS-CALD-05-116
. February 17, 2006.


"Maximal
Lattice Overlap in Example-Based Machine Translation,”
R.A. Hutchinson
, P.N. Bennett, J. Carbonell, P. Jansen, and R. Brown.

Carnegie
Mellon University
Technical Report CMU-CS-03-138. June 6, 2003.



Invited Talks

"An Exploration of Penalized Likelihood Estimation for Occupancy Modeling,"
Computational Ecology and Epidemiology Study Group, Odum School of Ecology, University of Georgia, Athens, GA.  May 14, 2014.

"Machine Learning for Ecological Science and Environmental Policy", with T.G. Dietterich and D. Sheldon,

tutorial at the
International Conference on Machine Learning (ICML),
June 28, 2011.  (slides)

"Machine Learning Problems in Species Occupancy Modeling,"
SCHARP Brown Bag Series
, Fred Hutchinson Cancer Research Center, Seattle, WA.  March 25, 2010.  (slides)


"Hidden Process Models with Applications to fMRI Data,"
Biostatistics and Bioinformatics Seminar
, Fred Hutchinson Cancer Research Center, Seattle, WA.  March 24, 2010.  (slides)


"Hidden Process Models with Applications to fMRI Data," 
Topic Contributed Session, Joint Statistical Meetings (JSM), Washington, DC.  August 2, 2009.  (slides)



Other Talks and Posters

"Site occupancy models with regression trees (OD-BRT): A comparison with standard site occupancy models (OD) and boosted regression trees (BRT)", 
Ninety-seventh Annual Meeting of the Ecological Society of America (ESA)
, Portland, OR, August 9, 2012.


"Incorporating Boosted Regression Trees into Site Occupancy Models," 
AVES Seminar
, Department of Fish and Wildlife, Oregon State University, Corvallis, OR.  November 17, 2011.  (slides)


"Incorporating Boosted Regression Trees into Ecological Latent Variable Models,"
Twenty-fifth Conference on Artificial Intelligence (AAAI)
, San Francisco, CA.  August 11, 2011.  (slides)


"Combining Boosted Regression Trees and Hierarchical Species Occupancy Models," (talk and poster), 
International Conference on Computational Sustainability, Massachusetts Institute of Technology, Cambridge, MA.  June 27, 2010.  (poster)


"Parameter Estimation in a Hierarchical Model for Species Occupancy,"
(poster with T.G. Dietterich),
Neural Information Processing Systems (NIPS) Workshops: The Generative and Discriminative Learning Interface
, Whistler, BC.  December 12, 2009.  (abstract


"Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models," (poster with T.M. Mitchell), 
Statistical Analyses of Neuronal Data Workshop (SAND) 2008, Pittsburgh, PA.  May 30, 2008.  (slides


"Hidden Process Models for Analyzing fMRI Data,"
Graduate Student Seminar Series
, Carnegie Mellon
School of Computer Science.  May 11, 2007. (slides)

"Hidden Process Models: Decoding Overlapping Cognitive States with Unknown Timing,"
Neural Information Processing Systems (NIPS) Workshops:
New Directions on Decoding Mental States from fMRI Data, Whistler, BC.  December 8, 2006. (slides)


"Hidden Process Models," 
Women in Machine Learning Workshop (WIML), San Diego, CA.  October 4, 2006.  (slides)


"Hidden Process Models,"
International Conference on Machine Learning (ICML)
2006, Pittsburgh, PA.  June 28, 2006.  (slides)


"Learning to Identify Overlapping and Hidden Cognitive Processes from fMRI Data,” (poster with T.M. Mitchell and I. Rustandi),
Human Brain Mapping (HBM)
2005, Toronto, ON.  June 2005. (slides


“Using Hidden Process Models to Decode Cognitive States from fMRI Data,”
Brain Science Seminar
, Carnegie Mellon University.  April 2005.


"Hidden Process Models for Body Monitoring Data," 
BodyMedia, Inc., Pittsburgh, PA.  March 2005. (slides)



Teaching

Instructor for Analysis of Algorithms (CS325 at Oregon State University), Summer 2013.

TA for Artificial Intelligence (undergraduate level), Spring 2007

TA for Machine Learning (undergraduate/master's level), Fall 2006


Service
Board Member (Chair) for the Oregon State Postdoctoral Association (2013-2014).  

Board Member (Committee Coordinator) for the Oregon State Postdoctoral Association (2012-2013)
.  

Program Committee Member for the 1st annual NorthEast Student Colloquium on Artificial Intelligence (NESCAI) 2006.  

Journal reviewing: NeuroImage, Computational Neuroscience, Ecology, Ecosphere.  

Conference/workshop reviewing: International Conference on Machine Learning (ICML), NorthEast Student Colloquium on Artificial Intelligence (NESCAI), Women in Machine Learning Workshop (WiML).  

Grant reviewing: National Science Foundation (NSF).