Associate Professor at the Institute for Genome Sciences, Program for Personalized and Genomic Medicine, Greenebaum Comprehensive Cancer Center, Department of Medicine, University of Maryland School of Medicine.
Interested in Human population genomics and history.
Interested in genomics and population genetics related to human diseases especially malaria.
Interested in deep generative models and representation learning.
Interested in population and quantitative genetics.
Interested in identifying natural selection in recently admixed populations.
Interested in deep learning of the epidemiology of HIV in Africa.
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Currently a Postdoctoral Fellow with Dr. Ivan Ovcharenko at the National Center for Biotechnology Information, National Institutes of Health.
Currently a Bioinformatics Analyst at the National Cancer Institute, National Institutes of Health.
Currently a Bioinformatics Analyst at the National Cancer Institute, National Institutes of Health.
Interested in the use of genomics and populations genetics to better understand human disease, and specifically cancer diagnosis and treatment. Also interested in better understanding of how differences in genetic background between human populations influence disease incidence rates and biology.
Interested in studying human demographic history, particularly population founding events and migration.
Interests in software development and project management specializing in next-gen sequencing analysis (including transcriptomics, small ncRNA, exome, genome wide association and SNP analysis).
Interested in the application of machine learning to multi-omic data in order to make inferences regarding disease risk, disease-related biological pathways, and demographic history. In addition, interested in the genetic epidemiology of complex diseases in diverse human populations.
Interested in studying how ancestry influences risk for complex diseases, especially in diverse populations.
Interested in deep learning, machine learning, and brain computer interfaces.
Interested in cancer genetics.