Faculty members with diverse research backgrounds and experiences contribute to the Division of Nephrology and Center for Immunity, Inflammation and Regenerative Medicine (CIIR) at the University of Virginia. Our core faculty consists of basic scientists with expertise in basic immunology, regenerative medicine, and stem cell biology, and clinician investigators with expertise in translational research in immunity and inflammation. Additionally, the CIIR has affiliated members from various departments throughout the School of Medicine.
Choose a faculty member to view his or her research profile. Links go to the School of Medicine Research Faculty Directory; use back button to return to the Nephrology division website.
Natural Killer Cells, Viral Immunity, Genetic basis of host resistance to viral infection, Tumor immunity, Immune cell regulation
Hypertension and kidney disease
Role of Microparticles in hypertension and vascular disease
Human lymphocyte biology and autoimmunity
Immune System Modulation
Contrast enhanced ultrasound in patients with kidney disease.
Basic Transplant Immunology; Role of Naturally occurring IgM antibodies in Acute Kidney Injury and transplant rejection.
Survival Analysis; longitudinal data analysis; latent variable analysis and mixture modeling; clinical trial design; Outcomes research
Immune mechanisms of acute kidney injury and fibrosis. Pulsed ultrasound in acute kidney injury
Pathogenesis of acute kidney injury; role of PPAR alpha in AKI and the role of pericytes in progressive fibrosis.
Immunological mechanisms of acute kidney injury and progressive kidney disease
Regulatory T Cell biology in kidney diseases and autoimmune diseases.
Macrophages, dendritic cells, and other myeloid cells interactions with glomerular parenchymal cells.
Inflammation, fibrosis, progression of kidney disease, diabetic nephropathy, cardiovascular disease, pathologic calcification, kidney transplantation
Clinical epidemiology, outcomes research, and racial/ethnic disparities; Models for survival, longitudinal and clustered data.