Welcome! I am an Assistant Professor of Statistics at the University of South Carolina. From 2018 to 2020, I was a postdoc at the University of Pennsylvania, supervised by Yong Chen and Mary Boland. I received my PhD in Statistics from the University of Florida in 2018 under the supervision of Malay Ghosh. I completed my Bachelor’s degree at Cornell University and a Master’s degree at the University of Massachusetts Amherst, and I also worked previously in industry as an engineer and as a financial analyst.

My methodological and theoretical research focuses on high-dimensional modeling and scalable machine learning algorithms for large and complex data sets. My recent work has been on developing flexible (mostly Bayesian) methods that relax assumptions such as linearity, Gaussianity, and/or independence. My applied research focuses on meta-analysis, spatiotemporal modeling, and analysis of electronic health records.

Curriculum vitae | Google Scholar | Twitter

Recent News

  • July 2021: Chapter on spike-and-slab lasso methods (with Veronika Ročková and Edward I. George) to appear in the Handbook of Bayesian Variable Selection.
  • May 2021: “Individual- and neighborhood-level risk factors for severe maternal morbidity” (with Jessica R. Meeker, Silvia P. Canelón, Lisa D. Levine, and Mary R. Boland) published in Obstetrics & Gynecology.
  • April 2021: “On the beta prime prior for scale parameters in high-dimensional Bayesian regression models” (with Malay Ghosh) published in Statistica Sinica.

Recent and Upcoming Talks

  • December 2021: CFE-CMStatistics 2021
  • November 2021: Fifth EAC-ISBA Conference
  • November 2021: Biostatistics Seminar, Virginia Commonwealth University
  • October 2021: Statistics Seminar, University of Minnesota
  • September 2021: ICSA Applied Statistics Symposium
  • August 2021: Joint Statistical Meetings
  • June 2021: 2021 ISBA World Meeting
  • April 2021: Statistics Seminar, University of California, Davis