Robert McCulloch

Biography

Robert McCulloch's research focuses on Bayesian statistics. In the Bayesian approach, you write down a full joint distribution for all quantities of interest and then condition on the knowns. The computational revolution has made this strategy feasible in complex, high dimensional problems. Much of McCulloch's recent research is on Bayesian approaches for tree-based ensemble models. Tree based methods have emerged as a basic tool in Machine Learning because they are a relatively simple way to uncover complex nonlinear relationships in high dimensional problems.  Ensemble methods combine many tree models into one overall model which is far more powerful than any one tree model can be on its own.

Recent applications look at personalized medicine, selection of long term portfolios (pensions), and scale conversion for Marketing data.

Education

Ph.D. University of Minnesota 1985

Courses

Summer 2019
Course Number Course Title
STP 792 Research
Spring 2019
Course Number Course Title
STP 493 Honors Thesis
STP 494 Special Topics
STP 590 Reading and Conference
STP 592 Research
STP 593 Applied Project
STP 598 Special Topics
STP 792 Research
APM 792 Research
STP 799 Dissertation
APM 799 Dissertation
Fall 2018
Course Number Course Title
STP 590 Reading and Conference
STP 593 Applied Project
STP 595 Continuing Registration
STP 792 Research
APM 792 Research
STP 799 Dissertation
APM 799 Dissertation
Spring 2018
Course Number Course Title
STP 493 Honors Thesis
STP 494 Special Topics
STP 593 Applied Project
STP 598 Special Topics
APM 792 Research
STP 792 Research
APM 799 Dissertation
Fall 2017
Course Number Course Title
STP 593 Applied Project
STP 595 Continuing Registration
APM 792 Research
Spring 2017
Course Number Course Title
STP 598 Special Topics