Our lab performs clinical research on people living with diabetes. Most of the work is related to improving the care of people with diabetes while in the hospital, or predicting and preventing hospital and emergency department visits.  

Our lab studies how where people live interacts with their behaviors and biology to affect their risk of developing cancer. We use advanced tools such as machine learning and mapping (geospatial methods) to find patterns in large sets of data. These patterns help us improve our ability to predict who might get cancer, and helps guide cancer prevention efforts to the people and places that need them most. We look at many kinds of data, including personal health, habits, genetics, markers in blood, and neighborhood conditions, to better understand cancer risk and why some people or communities have worse cancer outcomes than others. We don’t just look at the numbers—we use the information to take action and to work with patients and our community to create plans to lower cancer risk and improve health. The goal of our research is to work with data to support more targeted health solutions for everyone.

Learn more about our lab.

My research interests include health informatics, healthcare operations, data analytics, clinical decision analysis, and system modeling in healthcare services. My work has examined practice variance and systems analysis for quality and process improvement and established new clinical guidelines. Also, I have focused on health policy analysis, resource allocations of health services, and best practices in healthcare services. My research uses large datasets and clinical observations from various healthcare databases and field studies in clinical facilities. I have collaborated with hospitals, healthcare research institutes, and healthcare delivery organizations in the U.S. and foreign countries.