Badri N. Vardarajan, PhD, MS

  • Assistant Professor of Neurological Science (in Neurology, the Gertrude H. Sergievsky Center, and the Taub Institute)
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Overview

Dr. Vardarajan is bioinformatician by training, and his primary interests is to understand the role of genetic variation in the biology of neurodegenerative diseases, in particular, Alzheimer’s disease. His research group applies computational approaches for gene discovery in Alzheimer's disease (AD) in multi-ethnic populations. Dr. Vardarajan’s team is involved in several multi-institutional studies of genetics of AD including the Alzheimer’s Disease Sequencing Project (ADSP). He is applying computational pipelines to characterize structural variation in large scale sequencing data for gene discovery in Alzheimer’s disease. Dr. Vardarajan also leads multi-omics integration of genetic, transcriptomic, proteomic, metabolomics data for gene and pathway discovery in multiple cohorts including the EFIGA (Caribbean-Hispanic families) and WHICAP (Washington Heights-Inwood Columbia Aging Project).

Academic Appointments

  • Assistant Professor of Neurological Science (in Neurology, the Gertrude H. Sergievsky Center, and the Taub Institute)

Credentials & Experience

Education & Training

  • Undergraduate, 2003 University of Delhi
  • MS and PhD, 2012 Bioinformatics, Boston University
  • MS, 2016 Patient Oriented Research, Columbia University

Honors & Awards

  • 09/2016-08/2019 Peer Reviewed Alzheimer’s Research Program (PRARP) Convergence Science Research Award, Department of Defense
  • 07/2015-06/2017 Alzheimer’s Disease New Investigator Research Award
  • 07/2014-06/2016 KL2 Mentored Career Development Award, NIH
  • 04/2013-03/2014 Sergievsky Center Pilot Grant, Columbia University

Research

  • Gene and variant discovery in Alzheimer’s Disease using next-generation sequencing technologies.
  • Functional genomics in Alzheimer’s Disease
  • Multi-omics integration in complex disease
  • Identification of novel biomarkers of Alzheimer’s Disease
  • Translation of genetic findings to actionable drug targets