National Institute of Statistical Sciences - Independent Research Organization
The National Institute of Statistical Sciences (NISS) is an independent research organization providing expert research in science and public policy to academia, industry, and government. NISS fosters cross-disciplinary and cross-sector research in statistical and data sciences, connecting professionals for collaborative advancements.
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Presentation Transcript
www.niss.org Overview The National Institute of Statistical Sciences (NISS) is an independent research organization that serves as a neutral, objective expert in delivering research in science and public policy to its affiliates in academia, industry and government. NISS identifies, catalyzes and fosters high-impact cross- disciplinary and cross-sector research involving the statistical and data sciences.
www.niss.org The NISS Affiliate Program Brings together statistical, mathematical and data science professionals from all sectors academia, industry, government / national labs to support research, information dissemination, human resource development and networking. Affiliates take advantage of events NISS has in the pipeline or work to define new opportunities that will address their needs, and likely the needs of NISS colleagues as well.
www.niss.org People James L. Rosenberger (Director), Nell Sedransk (Director-DC) Mary Batcher (Board of Trustees Chair), Raymond Bain (Vice Chair), Christy Chuang-Stein (Affiliates Cmte Chair) Board of Trustees James Booth (Cornell U) Kate Crespi (UCLA) Jan Hannig (UNC) Nicholas Jewell (UC Berkeley), Mimi Kim (Einstein) Dennis Lin (PSU) Bhramar Mukherjee (U Michigan) Jerry Reiter (Duke U) Hal Stern (UC Irvine) Ron Wasserstein (ASA) Alyson Wilson (NCSU) Sam Woolford (Bentley U) Tim Hesterberg (Google) Leland Wilkinson (H2O) Gabriel Huerta (Sandia) Phil Kott (RTI) Tommy Wright (Census)
www.niss.org Motivation 1990 IMS Report Domain knowledge and statistical theory and methods are inseparable. The continued health of statistics depends strongly on continuing cross-disciplinary research in many fields. Close collaborations among statisticians and scientists push forward the frontiers. Constrained resources and existing infrastructure within academia, government and industry thwart growth and development of the needed cross-disciplinary (and cross-sector) research.
