Ryan McGranaghan
- ORCiD
- https://orcid.org/0000-0002-9605-0007
- OpenAlex ID
- https://openalex.org/A5065824713 (API record)
Associated Concepts [?]
- Semantic network (submitted by https://orcid.org/0000-0002-8424-0604)
- Physics
- Computer science
- Geology
- Geography
- Astronomy
- Engineering
- Quantum mechanics
- Geophysics
- Meteorology
- Operating system
- Mathematics
- Magnetic field
- Environmental science
- Biology
- Plasma
- Nuclear physics
- Philosophy
- Ionosphere
- Linguistics
- Space (punctuation)
- Geodesy
- Space weather
- Aerospace engineering
Authored Works
sorted by decreasing year, and then by display-name
- Space Weather: Complexity science, convergence research, and a risk and resiliency framework
- Infrastructure for 21st century science: Towards a Heliophysics knowledge commons
- Heliophysics Network Building UtilitiesA Contribution to the Heliophysics KNOWledge Network (Helio-KNOW), Natural Language Processing and Knowledge Graphs of Heliophysics research
- Developing a Vision for Maturing the Heliophysics Infrastructure towards Open Science: The DIARieS Analysis Ecosystem.
- Understanding the interconnected space weather system: The Convergence Hub for the Exploration of Space Science (CHESS) project and workshop
- Toward a Heliophysics Knowledge Commons: The Heliophysics KNOWledge Network (Helio-KNOW) and what it means for the future of Earth and Space Science
- Report on a Workshop to Understand Heliophysics Research Infrastructure
- NEREID: Converging in the Spaces Between
- Modeling Low-Earth Orbit Satellite Trajectories: Atmospheric Density Specification and Vehicle Environment Interactions
- Mapping Heliophysics Knowledge: Using Knowledge Graphs for Heliophysics Literature
- Heliophysics: A small field with big data science
- Ground magnetic field perturbation forecasting based on deep learning on spherical harmonics decomposition
- Enhancing the Estimation of GICs Over North America Using the Spherical Elementary Current System Technique.
- Assessing Critical Risk Indicators for Space Weather and the Power Grid with Outage Data in Massachusetts and Vermont
- A Next Generation Space Weather Particle Precipitation Model: Mature machine learning approaches, multiscale mesoscale prediction, and an open science framework for machine learning
Linked Co-Authors
- A. J. Halford
- A. K. Higginson
- Adam Kellerman
- Asti Bhatt
- Ayris Narock
- B. J. Thompson
- Banafsheh Ferdousi
- Brian L. Thomas
- Chigomezyo M. Ngwira
- Christopher Bard
- D. A. Roberts
- E. K. Sutton
- Enrico Camporeale
- Erika Palmerio
- J. Dorelli
- J. Ireland
- J. M. Weygand
- J. W. Gjerloev
- Jacob Bortnik
- Joseph Hughes
- Karthik Venkataramani
- L. K. Jian
- M. B. Cohen
- M. C. Damas
- M. J. Owens
- M. Pilinski
- R. M. Candey
- Rebecca Ringuette
- S. F. Fung
- Samuel J. Klein
- Samuel J. Schonfeld
- Spencer Hatch
- V. Ledvina
- Vishal Upendran
- W. Kent Tobiska
Linked Collaborating Institutions
- ADNET Systems Inc., Greenbelt, Maryland
- Atmospheric & Space Technology Research Associates (ASTRA)
- Catholic University, Washington DC
- Dartmouth College, New Hampshire
- Georgia Institute of Technology
- Inter-University Centre for Astronomy and Astrophysics, India
- Johns Hopkins University, Applied Physics Laboratory
- Lockheed Martin, Palo Alto
- NASA Goddard Space Flight Center, Maryland
- NASA HQ
- National Center for Atmospheric Research, High Altitude Observatory
- National Oceanic and Atmospheric Administration, Boulder
- Natural Resources Canada
- New Jersey Institute of Technology
- New Mexico State University
- Predictive Science Inc., California
- Queensborough Community College, New York
- Rutgers University, New Jersey
- Stanford Research Institute, California
- University of Bergen, Norway
- University of Calgary, Canada
- University of California, Los Angeles
- University of Colorado, Boulder
- University of Michigan
- University of New Hampshire
- University of Oxford, UK
- University of Reading, UK
- Virginia Polytechnic Institute and State University
- Wright State University, Ohio
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