Brian G. Vegetabile

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

I'm a fifth year PhD candidate studying statistics at the University of California, Irvine working under the advisement of Dr. Hal Stern. My research interests are in Bayesian inference and statistical machine learning techniques as they apply to causal inference in observational studies for studying human behavior. I am also passionate about statistical computing and data visualization. Recently, I have been investigating nonparametric techniques for estimating treatment assignment mechanisms in observational settings.

Publications

Elysia Poggi Davis, Stephanie A. Stout, Jenny Molet, Brian Vegetabile, Laura M. Glynn, Curt A. Sandman, Kevin Heins, Hal Stern, Tallie, Z. Baram (2017) | Early life exposure to unpredictable maternal sensory signals influences cognitive development: A cross-species approach, Proceedings of the National Academy of Sciences. http://doi.org/10.1073/pnas.1703444114

Manuscripts

Estimating the Entropy Rate of Finite Markov Chains with Application to Behavior Studies | Submitted | Brian Vegetabile, Jenny Molet, Tallie Z. Baram, Hal Stern | https://arxiv.org/abs/1711.03962

Presentations | Posters

Propensity Score Covariate Balancing with Gaussian Processes | with H. Stern | December 2017 | From 'What If?' To 'What Next?': Causal Inference and Machine Learning for Intelligent Decision Making | NIPS

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

Software

gpbalancer : an R Package for Optimally Balanced Gaussian Process Propensity Score Estimation

ccber : an R package for estimating the entropy rate of Markov chains for the Conte Center @ UC Irvine

Teaching

Incoming PhD Statistics Bootcamp | UCI Department of Statistics

Predictive Modeling with Python | UCI Data Science Initiative

Updated - November 2017