Dr. Anoop Mayampurath's research lab is focused on improving healthcare outcomes for hospitalized children, particularly by predicting cardiopulmonary deterioration. The lab is developing a new clinical decision support tool that uses machine learning to analyze electronic health records and provide real-time insights for healthcare providers. This tool aims to enable timely interventions, ultimately enhancing the quality of care for pediatric patients at risk.

Dr. Guanhua Chen's lab at the University of Wisconsin-Madison focuses on studying childhood asthma by analyzing the complex relationship between the microbiome and host genetics. They work with large datasets from infants to understand how these factors contribute to asthma risk and severity. The lab develops innovative statistical methods to improve our understanding of these interactions and hopes to inform new treatment strategies for asthma.

Dr. Mark W. Craven's lab focuses on harnessing advanced computational methods, particularly deep learning, to predict how genetic variations influence biological traits (phenotypes) across different scales. The research aims to enhance our understanding of human health and disease by improving genomic analyses, especially in the context of diseases resulting from rare genetic mutations. The lab collaborates with other research centers to build a comprehensive dataset that maps genetic variants to their phenotypic impacts.