Dr. Albers’ group has two broad foci: understanding the underlying processes that generate biomedical—specifically clinically related—data and inventing and adapting computational machinery for scientists, clinicians, and patients to identify and understand of mechanistic features that govern clinical and physiologic systems driven by the need to aid in informed decision-making.
Dr. Bennett’s group focuses on clinical decision-making in high-risk environments such as intensive care units and on the development and implementation of informatics and data science methods and tools to improve outcomes.
Dr. Dwork's lab is focused on developing fast and robust medical imaging and radiation oncology technologies. The lab uses applied mathematics algorithms (e.g. optimization) to constrain the solution with known physics so that more information can be extracted from the collected data.
Dr. Ong's lab has extensive experience with record linkage methods including privacy preserving record linkage (PPRL) and data quality. He is the principal investigator of projects to develop record linkage methods and software solutions. Dr. Ong's other research interests include data harmonization, schema mapping, machine learning and natural language processing.
Dr. Sirlanci is interested in investigating problems arising in biomedicine by using data assimilation techniques. For this purpose, she uses both physiology-based mechanistic models and machine learning models.