Areas of Focus:

BioinformaticsBiological & MechanisticBiomarker DiscoveryCollaboration & InnovationCross-institutional CollaborationData-Driven & QuantitativeEarly Disease DetectionEnvironmental ExposuresExperimental Platforms & ModelsHuman CohortsHuman GeneticsImplementation ScienceMachine Learning & AIPopulation & Patient-CenteredPrecision MedicineReal-world EvidenceTranslational & ClinicalCross-Cutting & Special PopulationsPediatric Autoimmune DiseasesRare Autoimmune Diseases

  • Susan and Morris Mark Professor of Medicine, Department of Medicine, NYU Grossman School of Medicine / NYU Langone Health
  • Professor, Department of Population Health, NYU Grossman School of Medicine / NYU Langone Health
  • Co- Director, Division of Precision Medicine, NYU Grossman School of Medicine / NYU Langone Health


Dr. Morgan E. Grams is a nephrologist and PhD-trained epidemiologist. She is the Susan and Morris Mark Professor of Medicine at New York University, where she helps lead the Division of Precision Medicine, a multidisciplinary computational research unit. Her research spans multiple areas of medicine, using multimodal data and advanced statistical methods to address clinically meaningful questions.

She is the co-Principal Investigator of the CKD Prognosis Consortium (CKD-PC), a global consortium of over 250 investigators and 30 million patients. She has been honored with the Donald W. Seldin award from the American Heart Association and American Society of Nephrology, the Garabed Eknoyan award from the National Kidney Foundation, and induction into the American Society of Clinical Investigation. She is the US Chair of KDIGO, the global guideline organization for kidney disease.

Projects

Featured Pilot Projects

Early Detection and Diagnosis of Autoimmune Diseases Using Foundation AI Models
Project | New York University

Early Detection and Diagnosis of Autoimmune Diseases Using Foundation AI Models

Applying self-supervised AI to multi-modal electronic health records — integrating clinical notes, labs, and imaging — this project builds scalable diagnostic models to detect autoimmune diseases earlier and more precisely.