Dr Jason Kugelman

Dr. Jason Kugelman is a postdoctoral researcher in the Genomics, Imaging, and AI Lab at QIMR Berghofer, with a strong passion for leveraging artificial intelligence and machine learning to advance medical research and improve lives around the world. He has an extensive background in machine learning and data science, including research and industry experience in the areas of computer vision, medical image segmentation, generative machine learning, natural language processing, representation learning, and traditional machine learning approaches. His prior work has resulted in translational impact through the development and deployment of automated ocular image segmentation tools for optical coherence tomography (OCT) and conjunctival ultraviolet autofluorescence (CUVAF) images that are currently utilised by clinicians and researchers.

Dr. Kugelman was the recipient of an Outstanding Doctoral Thesis Award (ODTA) from the Queensland University of Technology for his PhD thesis investigating enhancements for the segmentation of the retinal layers and the choroid in OCT images using novel synthetic data augmentation techniques leveraging images constructed by generative machine learning models. His current research aims to employ multi-omics-based machine learning approaches with large datasets for early disease detection, future risk prediction, and novel biomarker discovery across a range of conditions, including cancer, cardiovascular diseases, and neurodegenerative disorders. With a particular interest in oculomics, he also seeks to understand how data from one organ system, such as the eye, can provide insight into the structure, function, and health of others, enabling the prediction of complex traits and the discovery of novel biological connections across the body.