I'm a machine learning scientist, currently working at FICO (formerly Fair Isaac) in San Diego.  Formely, I was with Evolved Machines, a startup in Palo Alto, CA, developing models of visual object recognition based on cortical microcircuitry.  Prior to that, I did my postdoct in Sebastian Seung's Lab in the MIT Department of Brain and Cognitive Sciences, developing algorithms for automatic reconstruction of neural circuity from electron microscope images.

My main research interest is in applying sparse coding and statistical learning algorithms to visual recognition and other inference problems, such as image reconstruction, imagination, and top-down expecatation-driven segementation. We have developed hierarchical, biologically-motivated dynamic networks for visual inference tasks.  My PhD thesis from UC San Diego in 2005 and later papers discuss this work.

In general, I'm interested in applying machine learning methods to challenging real-world problems. Examples include predicting failures in hard drives using nonparametric statistical tests, support vector machines (SVMs) and unsupervised clustering. I've also done work at the Scripps Institution of Oceanography (SIO) studying statistical patterns in the long-term tide record and wave modeling.

Resume (pdf, 1 page)
Academic CV (pdf, 3 pages)

I can be reached at:

7234 Shoreline Dr. Apt 150
San Diego, CA 92122
(858) 344-3329

Email: