Clinical Informatics/Digital Health: The Kamaleswaran Lab focuses on developing novel machine learning algorithms and applications in the area of sepsis, multi-organ failure and complex acute care. We focus on multi-omics analysis with an emphasis on transcriptomics (single cell RNASeq), metabolomics and metagenomics/microbiome. We further develop longitudinal and dynamical machine learning models of these multi-omics data to explain time-oriented changes in inflammatory markers that predict organ dysfunction among patients with sepsis. Together, these biomarker data are integrated with clinical electronic medical record and biosensor data to enrich phenotypes of sepsis for earlier recognition, targeted therapy and improved outcomes.
Rishikesan (Rishi) Kamaleswaran is an Assistant Professor at Emory University, Department of Biomedical Informatics, with secondary appointments in Pediatrics and Emergency Medicine. He was previously an Assistant Professor at the Center for Biomedical Informatics and Division of Critical Care Medicine at the University of Tennessee Health Science Center (UTHSC). He earned his Ph.D. in Computer Science from the University of Ontario Institute of Technology in Canada. Prior to moving to UTHSC, he was a research fellow at the Division of Neonatology and the Department of Critical Care Medicine at the Hospital for Sick Children (Toronto) where he led efforts on the collection and analysis of physiological data in the Neonatal Intensive Care Unit for multiple clinical conditions including neonatal hypoglyceamia, physiological deterioration, nosocomial infection, and apnoea of prematurity. His current interests include severe sepsis detection and multi-organ dysfunction syndrome. His contribution includes: clinical big data, real-time event stream processing, data analysis, data visualization and information systems design.