Brian G. Vegetabile

Ph.D. Candidate at the University of California, Irvine
bvegetab [atsymbol] uci [dotedu]

I'm a fourth year PhD candidate studying statistics at the University of California, Irvine working under the advisement of Dr. Hal Stern. My research interests are in statistical methods in observational studies. Recently, I have been investigating nonparametric techniques for estimating treatment assignment mechanisms in observational settings.

Publications | Papers

Estimating the Entropy Rate of Finite Markov Chains with Application to Behavior Studies | Submitted | Brian Vegetabile, Jenny Molet, Tallie Z. Baram, Hal Stern

Early life exposure to unpredictable maternal sensory signals influences cognitive development: A cross-species approach | In Revision | Elysia Poggi Davis, Stephanie A. Stout, Jenny Molet, Brian Vegetabile, Laura M. Glynn, Curt A. Sandman, Kevin Heins, Hal Stern, Tallie, Z. Baram

Presentations | Posters

A Gaussian Process Approach for Estimating Treatment Assignment Mechanisms | with H. Stern | August 2017 | Joint Statistical Meetings

Bayesian Estimation of Treatment Assignment Mechanisms with Gaussian Process Priors | with H. Stern | May 2017 | Atlantic Causal Inference Conference

An Overview of Statistical Approaches to Causation | February 2017 | UCI Space-Time Modeling Group

A Rapid and Informal Introduction to Python for Data Science | November 2016 | Cal State Fullerton

Estimation of Entropy Rate of a Finite Markov Process in a Biological System | with H. Stern | August 2016 | Joint Statistical Meetings

Estimation of Entropy Rate in a Biological System | with H. Stern | February 2016 | NIH Conte Center Review Board

Exploring and Visualizing Data: Techniques for a clearer presentation of data | July 2015 | UCI Data Science Initiative Mini Statistics Workshop

Chandra X-Ray Observatory Aspect Camera Assembly Star Acquisition Analysis | with T. Aldcroft | August 2014 | Harvard's Topics in Astrostatistics


Incoming PhD Statistics Bootcamp | UCI Department of Statistics

Predictive Modeling with Python | UCI Data Science Initiative

Last Updated - May 2017