Stanard’s research focuses on utilizing machine learning techniques to analyze digitized blood stain patterns in collaboration with experts in forensic science. She holds a PhD in theoretical biophysics during which she used computational simulation to understand biological systems (static and dynamic behavious).

Stanard’s interest has recently shifted toward using AI on real life data. She gained extensive experience working on digitized blood stains which primed her for her current role. She worked at university clinic of cologne using deep learning to classify aberrations within WBC (white blood cells) in PBS (peripheral blood sample) from patients suffering from CLL (Chronic Lymphocyte Leukemia). Additionally, she has used supervised machine learning to help identify the most important prognostic factors on CLL and build a prognostic scoring model that can assist clinicians making better decision on personalized treatment for CLL patients.

She strives to improve her skills and aspiring to become an expert in the field.