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1 April 2017 16 views No Comment
Yili Hong, JSM Program Chair-Elect, and Ying Hung, SRC Program Chair

    The Physical and Engineering Sciences Section (SPES) is sponsoring the following two P.M. roundtable sessions at JSM 2017 in Baltimore:

    Design of Experiment for Big Data Era
    Dennis Lin, Pennsylvania State University

    Classical design of experiments is mainly for agricultural and industrial problems, which may not be appropriate for the Big Data era of today. We will first discuss what is new for Big Data–type problems and then talk about future directions for design of experiments for the new environment.

    Statistical Challenges and Opportunities with Remote Sensing Data
    Jon Hobbs, NASA Jet Propulsion Laboratory

    Remote sensing instruments can provide high-resolution and high-volume data to inform numerous physical and environmental processes. Typically, the quantities of interest—such as the composition of the Earth’s or other planetary atmosphere—must be inferred from the information in satellite radiance spectra. The inference can often involve complex, nonlinear, computationally expensive physical models, so a variety of tools for uncertainty quantification is used. Understanding the sources of uncertainty can provide additional insight for the scientific applications that benefit from the use of satellite data. This discussion will address the trade-offs between making optimal inference and practical considerations such as data volume for global remote sensing efforts.

    If you are interested in attending roundtables at JSM, registration is required.

    Spring Research Conference

    The 24th IMS/ASA Spring Research Conference (SRC) on Statistics in Industry and Technology will take place May 17–19 at Rutgers University.

    The purpose of SRC is to promote research in statistical methods that address problems in industry and technology and to stimulate interactions among statisticians, researchers in the application areas, and industrial practitioners. The conference has a history of more than two decades and has explored many interesting and important topics in research and applications.

    Keynote speakers will be Vijay Nair of the University of Michigan and David Madigan of Columbia University. Xiao-Li Meng of Harvard University will speak at the conference banquet.

    There are 20 invited sessions and four contributed sessions with topics such as design of experiments, modern computing, uncertainty quantification, computer experiments, recent advances in statistical learning, network sampling, data fusion, time series for business problems, experimental design and causal inference in high-tech companies, and methods on quality improvement and measurement system.

    Program details and registration information are available on the Rutgers website.

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