Patrick Giolando is currently a Biomedical Engineering Ph.D. student at the University of Texas at Austin. Before joining the Castillo Lab at UT Austin, Patrick Giolando completed a thesis Master of Science in Mechanical Engineering (2019-2021) and a Bachelor of Science in Biomedical Engineering (2014-2018) from Purdue University. During his time at Purdue University, he studied an array of mathematical and computational models in biomedical engineering, ranging from modeling protein signal transduction in the post-synaptic density to modeling two-way coupled flow for the prediction of the motion of cells suspended in flow.
During Patrick’s first year at UT Austin his research focused on developing machine learning models for material parameter identification of highly nonlinear brain tissue by indentation. After joining Dr. Castillo’s Dynamic Medical Image and Computing Lab, Patrick is focused on applying his computational background to advancing the field of Imaging Sciences. Current research aims to create a pipeline for clinicians to quantify the change in mechanical behavior of lung tissue from non-contrast 4DCT scans. By monitoring the changes in the behavior of a patient’s lung tissue over time, disease progression can be detected at its earliest stages, as well as provide targets for therapeutic interventions.