Jason H. Moore

ORCID iD
https://orcid.org/0000-0002-5015-1099
  • Country
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United States

Sources:
Jason H. Moore (2017-05-26)

  • Keywords
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Artificial Intelligence,

Sources:
Jason H. Moore (2017-05-26)

Bioinformatics,

Sources:
Jason H. Moore (2017-05-26)

Biomedical Informatics,

Sources:
Jason H. Moore (2017-05-26)

Complex Adaptive Systems,

Sources:
Jason H. Moore (2017-05-26)

Genetic Epidemiology,

Sources:
Jason H. Moore (2017-05-26)

Genomics,

Sources:
Jason H. Moore (2017-05-26)

Human Genetics,

Sources:
Jason H. Moore (2017-05-26)

Machine Learning,

Sources:
Jason H. Moore (2017-05-26)

Statistical Genomics

Sources:
Jason H. Moore (2017-05-26)

  • Websites
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Computational Genetics Laboratory

Sources:
Jason H. Moore (2017-05-26)

Epistasis Blog

Sources:
Jason H. Moore (2017-05-26)

  • Other IDs
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Scopus Author ID: 7405241093

Sources:
Scopus - Elsevier (2017-06-06)

Biography

Jason Moore is the Edward Rose Professor of Informatics and Director of the Penn Institute for Biomedical Informatics. He also serves as Senior Associate Dean for Informatics and Chief of the Division of Informatics in the Department of Biostatistics, Epidemiology, and Informatics. He came to Penn in 2015 from Dartmouth where he was Director of the Institute for Quantitative Biomedical Sciences. While at Dartmouth he founded their bioinformatics core facility and built the university’s first campus-wide high-performance computer system. Prior to Dartmouth he served as Director of the Advanced Computing Center for Research and Education at Vanderbilt University where he launched their first high-performance computer. He has a Ph.D. in Human Genetics and an M.S. in Applied Statistics from the University of Michigan. He leads an active NIH-funded research program focused on the development of artificial intelligence and machine learning algorithms for the analysis of complex biomedical data. In addition to an active research program, Dr. Moore is committed to undergraduate and graduate education. He has trained more than 75 students and postdocs and has founded several interdisciplinary training programs. He is an elected fellow of the American Association for the Advancement of Science (AAAS), an elected fellow of the American College of Medical Informatics (ACMI), an elected fellow of the American Statistical Association (ASA), and was selected as a Kavli fellow of the National Academy of Sciences (NAS). He is Editor-in-Chief of the journal BioData Mining.
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