The Mathioudakis lab is focused on developing and evaluating clinical decision support systems, technology, and mHealth for diabetes prevention and management. Our lab leverages large electronic medical record databases and uses machine learning algorithms and artificial intelligence to identify patterns in clinical care associated with optimal clinical outcomes. We are interested in understanding the role that advanced diabetes technologies can play in improving health outcomes for patients with diabetes. Our lab has published extensively on outcomes related to diabetes prevention and diabetes management and outcomes. Based on data from our long-term (over 10 year) clinic-based prospective cohort study from the Johns Hopkins Multidisciplinary Diabetic Foot and Wound Clinic, we have published extensively on clinical predictors and outcomes of patients with diabetic foot ulcers, focusing specifically on the role that glycemic control plays in patients with this complication. Healthcare disparities exist throughout medicine, but are particularly prominent in diabetes; our lab has evaluated healthcare inequities in diabetes outcomes and is developing and evaluating strategies to overcome them. In addition to identify optimal management approach to diabetes and its complications, our lab is interested in development and evaluation of innovative technology approaches to diabetes prevention.

Researchers in the Kathleen Sutcliffe Lab study organizational adaptability, reliability and resilience. Our work examines how factors such as management teams, group dynamics, information search processes, communication and learning processes affect organizational performance. Our team also studies how an organization’s design and culture affect members’ abilities to sense, manage and respond to dynamic demands. Additionally, our work seeks to better understand the factors that promote individual and organizational resilience.

Our laboratory is interested in understanding the neural basis of auditory perception and vocal communication in a naturalistic environment. We are interested in revealing neural coding mechanisms operating in the cerebral cortex and how cortical representations of biologically important sounds emerge through development and learning.