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Spotlights

 

Graduating PhD Student Spotlight: Jennifer Starling

JENNIFER STARLING PhD in Statistics, UT Austin (Spring 2020)MS in Statistics, Texas A&M UniversityBS in Mathematics, Virginia TechDissertation: "Bayesian methods for complex data structures, with applications to precision medicine in women’s healthcare"Dissertation Advisor: Dr. James ScottResearch Interests: Bayesian methods, nonparametric regression, tree-based models, causal inference, public health, women's health, obstetricsWebsite: https://jestarling.github.ioWhat does your research focus...

Jennifer Starling: SBSS AWARD WINNER

23 January 2020—Statistics doctoral candidate Jennifer Starling has been selected as one of ten Section of Bayesian Statistical Science (SBSS) student paper award winners for Joint Statistical Meetings 2020.  Jennifer is advised by Dr. James Scott. Her paper is titled "BART with Targeted Smoothing: An analysis of patient-specific stillbirth risk"...

SDS Seminar Series - Jennifer Starling

Title: Smooth extensions to BART, with applications to women's healthcare practice and policyAbstract: Bayesian Additive Regression Trees (BART) has been shown to be an effective framework for modeling nonlinear regression functions, with strong predictive performance in a variety of contexts. The BART prior over a regression function is defined by independent...

A Growth Mindset Intervention Can Change Students’ Grades if School Culture is Supportive

Article from College of Natural Science News, August 09, 2019: Boosting academic success does not have to derive from new teachers or curriculum; it can also come from changing students' attitudes about their abilities through a short online intervention, according to the latest findings from the National Study of Learning Mindsets...
Jennifer Starling Gives Invited Talk at the 2019 Joint Statistical Meetings

Jennifer Starling Gives Invited Talk at the 2019 Joint Statistical Meetings

15 August 2019— Doctoral student Jennifer Starling gave an invited talk on her research, titled "Targeted Smooth Bayesian Causal Forests for Heterogeneous Smooth Treatment Effects," at the 2019 Joint Statistical Meetings held in Denver, Colorado during July 27 – August 1, 2019. The work presented extends the Bayesian Causal Forest framework to include cases where...

Jennifer Starling wins the Thomas R. Ten Have Award

30 May 2018—Jennifer Starling was presented with the Thomas R. Ten Have Award at the Atlantic Causal Inference Conference held at Carnegie Mellon University May 21- 23, 2018, for her poster titled “Functional BART for Causal Inference” in collaboration with Jared S. Murray, Patricia A. Lohr, Abigail R.A. Aiken, Carlos M. Carvalho, and...

Student Spotlight: Jennifer Starling

  14 November 2016—Meet Jennifer Starling, a PhD student in the Department of Statistics and Data Sciences. Tell us a little bit about yourself—educational background, previous work experience, etc. I am from Des Moines, Iowa. I graduated from Virginia Tech in 2006 with degrees in math and theatre. Afterwards, I spent several...