Research Objectives

 

  1. To understand the tempo and mode of craniofacial evolution, particularly along the dinosaur-bird transition.

  2. To elucidate the complex interplay between anatomical changes along developmental and evolutionary time scales

  3. To investigate both practical and theoretical issues in phylogenetics and geometric morphometrics through the development of analytical tools.

 

I pursue answers to these broad evolutionary topics by combining techniques from comparative anatomygeometric morphometrics, and computational biology.

Comparative Anatomy

Anatomical descriptions of species are at the core of paleontological studies and collectively provide important data for making generalizations about biological processes. Studying organisms in a comparative framework illuminates the evolutionary narrative underlying anatomical structures. While direct examination of specimens is essential for accurate and detailed descriptions, I enhance our understanding of both living and extinct organisms by utilizing cutting-edge imaging techniques, including high-definition surface scans, X-ray computed tomography (XRCT) scans, new staining protocols such as the diffusible iodine-based contrast-enhanced CT (diceCT) imaging for soft-tissue anatomy (https://dicect.com/), and bone histological analysis, which allows individuals to be aged by counting growth rings.

Geometric Morphometrics

Geometric morphometrics (GM) is the quantification, visualization, and statistical analysis of shape using coordinate points. I employ GM techniques to mathematically describe the often remarkable changes in form that occur during development of an organism as well as through evolutionary time. In my research, I collect three-dimensional coordinate data from specimens using various hardware and software. These data are then subjected to multivariate statistical toolkits and comparative phylogenetic methods to determine drivers of phenotypic evolution.

Computational Biology

 

As scientific data accumulate at an increasing rate, computational biology provides the analytical tools for processing and identifying patterns in massive data sets. Besides purely biological questions, I write analytical tools to conduct simulation and statistical tests on phylogenetic and morphometric data to determine how a particular practice or biological phenomenon impacts the results of analyses. A majority of these programs are written in R and Python languages. In particular, I am interested in exploring potential artifacts engendered by methodological practices in GM and phylogenetic analyses and developing tools for assessing and improving data quality.