Undergraduate USRI Intern

A consistent problem in human paleontology is the adherence of matrix and calcium carbonate to ancient skeletal material.  My 2024 summer internship was focused on using machine learning in ORS Dragonfly software to develop methods to automate the segmentation of calcium carbonate and matrix (dirt) adhering to bone from microCT scans of skeletal remains of the Uyun Al’ Hammam, an epipalaeolithic burial site in Northern Jordan.  My results demonstrate that it is possible to ‘virtually’ clean skeletal remains instead of using chemicals that can be destructive to the skeletal remains. Further research has been conducted on the segmented bone to calculate biomechanical properties of bone that include trabecular thickness, degree of anisotropy, total volume, bone volume function, trabecular separation. In addition to utilizing ORS Dragonfly’s Bone Analysis for conducting biomechanical properties, Bone-J programming is also utilized to conduct morphometric properties of trabecular bone to conduct a comparative analysis between the two programmes.
 
My research interests lies in the fields of biological anthropology and public health policy, mainly studying bone health, quality, and variation of modern and past populations to further understand our human skeletal biology and skeletal health outcomes. I wish to implement my growing knowledge within the public health field to continue promoting bone health for future generations. In addition, understanding how external factors, such as environment or individual choices can further affect human skeletal biology and skeletal health outcomes.