Frank has moved! Frank is now an assistant professor in the statistics department at Columbia University. His new homepage is here. Recent Highlights
A Hierarchical, Hierarchical Pitman-Yor Process Language Model
F. Wood and Y.W. Teh, ICML 2008 Workshop on Nonparametric Bayes Poster
A Nonparametric Bayesian Alternative to
F. Wood and M. J. Black, Journal of Neuroscience Methods, 173:1-12, 2008. PDF preprint
- Code: Dirichlet process mixture modeling MATLAB code (.zip, .tar.gz).
Accompanies the JNM paper above and includes an example spike sorting script.
Incremental Nonparametric Bayesian Regression
F. Wood, D. H. Grollman, K, A. Heller, O. C. Jenkins, and M. J. Black,
Brown University Dept. Computer Science Technical Report CS-08-07, 2008 PDF
My research effort is directed towards contributing models and algorithms to the field of statistical machine learning. My current applied research focus is on problems in neural data modeling, natural language processing, and robotics.
I believe that the conceptual symbiosis between neuroscience and computer science (particularly in machine learning) is still in its infancy. As a computer scientist I believe that the computational superiority exhibited by even the most simple biological organisms is a strong argument for doing research at the intersection of these two fields.
My style is to build machine learning algorithms that improve on the state of the art by drawing from scientific findings at all levels of scientific investigation (physics to psychology). I am particularly interested in pursuing the connections between specific features of Bayesian machine learning algorithms and the biological mechanisms they very much resemble.