Will Landecker

landeckw at cs dot pdx dot edu

I am a Ph.D. student in the computer science department of Portland State University. I am a member of Melanie Mitchell's research group, and I collaborate with the Synthetic Cognition team at Los Alamos National Laboratory.

Research

My research focuses on understanding and explaining the decisions of classifiers, particularly as they apply to computer vision systems. Rather than treating a classifier as a black box, I examine the interactions between data and classifiers in order to verify that classifiers are gleaning relevant information from the data rather than spurious statistics.

My broader research interests include:

Machine Learning
Computer Vision
Computational Neuroscience
Cryptography
Music Information Retrieval

Publications

2011

Will Landecker, Michael Thomure and Melanie Mitchell. Background cues in images classified by hierarchical models. Grand Challenges in Neural Computation II, 2011 (Workshop abstract and poster).

Michael Thomure, Will Landecker and Melanie Mitchell. Random prototypes in hierarchical models of vision. Grand Challenges in Neural Computation II, 2011 (Workshop abstract and poster).

Steven Brumby, Michael Ham, Will Landecker, Garrett Kenyon and Luís Bettencourt. Visualizing classification of natural video sequences using sparse, hierarchical models of cortex. Computational and Systems Neuroscience - COSYNE 2011 (Conference abstract and poster).

2010

Will Landecker, Steven P. Brumby, Mick Thomure, Garrett T. Kenyon, Luís M. A. Bettencourt and Melanie Mitchell. Visualizing classifications of hierarchical models of cortex. Computational and Systems Neuroscience - COSYNE 2010 (Conference abstract and poster).

2009

Steven P. Brumby, Garrett T. Kenyon, Will Landecker, Craig Rasmussen, Sriram Swaminarayan, and Luís M. A. Bettencourt. Large-scale functional models of visual cortex for remote sensing. 38th IEEE Applied Imagery Pattern Recognition Workshop, "Vision: Humans, Animals, and Machines," 2009 (Workshop paper).

2006

Convergence of the Baum Welch Algorithm and Applications to Music. Thesis, Reed College, B.A. Mathematics. Advisor: Jamie Pommersheim (Undergraduate thesis)

Teaching

Current term

Spring 2012: CS 546 - Advanced Topics in Machine Learning

Previous terms

Spring 2010: Teaching assistant - CS 581, Theory of Computation
Spring 2009: Teaching assistant - CS 251, Discrete Structures II
Winter 2009: Teaching assistant - CS 251, Discrete Structures II
Fall 2008: Teaching assistant - CS 250, Discrete Structures

Other

I also enjoy gardening, cooking, traveling, rugby (union), touch rugby, languages, music, and mushroom hunting.