Graduate Coursework at Carnegie Mellon University:

36-752 Advanced Probability, Steve Hanneke, Fall 2009
80-820 Computational Models of Cognition, David Danks and Clark Glymour, Fall 2009
10-702/36-702 Statistical Foundations of Machine Learning, Larry Wasserman and John Lafferty, Spring 2009
36-724 Applied Bayesian and Computational Methods, Surya Tokdar, Spring 2009
15-826 Multimedia Databases and Datamining, Christos Faloutsos, Spring 2009
10-708 Probabilistic Graphical Models, Carlos Guestrin, Fall 2008
15-853 Algorithms in the "Real World", Guy Blelloch, Fall 2008
36-711 Statistical Computing, Surya Tokdar, Fall 2008
80-812 Seminar on Causation, Clark Glymour and Peter Spirtes, Fall 2008
10-701/15-781 Machine Learning, Eric Xing, Spring 2008
36-708 Linear Models and Experimental Design, Jong Soo Lee, Spring 2008
36-911/80-815 Seminar in Foundations of Statistics: R.A. Fisher, Teddy Seidenfeld, Spring 2008
10-705/36-705 Intermediate Statistics, Matthew Harrison, Fall 2007
10-661/80-616 Probability and Artificial Intelligence, David Danks, Fall 2007
80-600 Minds, Machines and Knowledge, Horacio Arló-Costa, Fall 2007

Courses Audited at Carnegie Mellon University

45-814 Options, Duane Seppi, Fall 2009
21-651 General Topology, Giovanni Leoni, Fall 2009
21-620/621 Real Analysis and Lebesgue Integration, Jack Schaeffer, Fall 2008

Graduate Coursework at Tulane University (while undergrad):

MATH-603 Stochastic Processes, Zachariah Dietz, Spring 2007
NSCI/PSYC-657 Cognitive Neuroscience, Edward Golob, Spring 2007
NSCI/PSYC-609 Applied Statistics II, David Corey, Fall 2006
MATH/PHIL-607 Mathematical Logic, Graeme Forbes, Lagniappe 2006 (summer semester to make up for closing during Hurricane Katrina)
MATH/PHIL-694 Modal Logic and Montague Grammar, Graeme Forbes, Spring 2005