CEDAR email: CEDAR session 2017: Next generation systems science

[Mcgranaghan, Ryan (335G-Affiliate)]

Fellow CEDAR attendees,

We would like to invite you to participate in our 2017 workshop session, Next generation systems science<http://cedarweb.vsp.ucar.edu/wiki/index.php/2017_Workshop:Next_generation_systems_science>.

Understanding and modeling complex and highly coupled MIT phenomena requires a systems-level (global) approach and a wide range of expertise. Issues of deciphering complexity through systematic data utilization also confront fields such as economics, social sciences, and medicine, and their solution has overwhelmingly been to embrace novel mathematical tools and computational technologies to advance understanding. Our session will be a forum for promising and innovative new methods and their roles in creating new understanding of the entire geospace system.

We aim to bring together a multi-disciplinary audience of space physicists, computer scientists, and data scientists to discuss promising current and future efforts with the goal of establishing groups with necessary and diverse expertise to collaborate on compelling problems moving forward.

We will have three exciting scene-setting talks from:

  1.  Seebany Datta-Barua (innovative methods for ionosphere-thermosphere discovery - https://www2.hao.ucar.edu/sites/default/files/users/sheryls/S4%20Datta-Barua.pdf)
  2.  Chunming Wang (data mining approaches to improve medium-range ionosphere-thermosphere forecasts - https://ams.confex.com/ams/97Annual/webprogram/Paper313591.html)
  3.  Josh Semeter (scientific insight through computer-aided discovery - http://ieeexplore.ieee.org/document/7515118/?part=1)

We invite short talks highlighting innovative approaches to address the complexities of geospace systems science.

We would like to pose the following questions to excite potential contributors:

  1.  How do we develop new understanding of complex processes in the geospace system?
  2.  In what ways are new approaches, including the emerging fields of data fusion, data science, and machine learning, improving understanding of the geospace system?
  3.  What allows a more efficient and widespread utilization of the geospace observational system?
  4.  What are the challenges of applied data-driven methods for the MIT system?

Conveners:
Ryan McGranaghan
Tomoko Matsuo
Alex Chartier
Marcin Pilinski



Ryan McGranaghan | Jack Eddy Postdoctoral Research Fellow

          University Corporation for Atmospheric Research (UCAR)
          Jet Propulsion Laboratory
          4800 Oak Grove, M/S 138-314  |  Pasadena, CA 91109
          818.354.0926  |  rymc1012 at ucar.edu<mailto:rymc1012 at ucar.edu>  / ryan.mcgranaghan at jpl.nasa.gov<mailto:ryan.mcgranaghan at jpl.nasa.gov> |  cpaess.uc<http://cpaess.ucar.edu/>ar.edu<http://cpaess.ucar.edu/>

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