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Ryan McGranaghan
Principal Data Scientist/Aerospace Engineering Scientist at ATMOSPHERIC AND SPACE TECHNOLOGY RESEARCH ASSOCIATES, LLC
Ryan McGranaghan is a senior Data Scientist at NASA Jet Propulsion Laboratory, specializing in aerospace engineering and data science.1 His career has focused on space weather, ionospheric research, and the application of data science to aerospace challenges.
Career Highlights
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Current Position: Senior Data Scientist and Aerospace Engineering Scientist at NASA Jet Propulsion Laboratory (since January 2023)1
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Previous Role: Principal Data Scientist/Aerospace Engineering Scientist at ATMOSPHERIC AND SPACE TECHNOLOGY RESEARCH ASSOCIATES, LLC (January 2019 - January 2023)1
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Postdoctoral Experience: Jack Eddy Postdoctoral Fellow at NASA Jet Propulsion Laboratory (January 2017 - January 2019)1
Education and Research
Ryan holds a Ph.D. from the University of Colorado Boulder, where he completed his studies between 2011 and 2016.1 His research has focused on ionospheric and atmospheric remote sensing, as well as space environment data analysis.
Achievements and Recognition
- Selected for the Young Scientist Award by the International Union of Radio Science (URSI) in 20171
- Gave a TEDx talk at TEDxCU in April 20151
- Awarded the Vela Fellowship to attend the Space Weather Summer School at Los Alamos National Laboratory in 20141
Recent Developments
In 2024, Ryan announced that he had been selected to serve as the US Science Envoy for Artificial Intelligence, indicating his growing influence in the field of AI and its applications to space science.2
Ryan McGranaghan is known for his work at the intersection of data science, artificial intelligence, and space research, contributing to advancements in understanding space weather and ionospheric phenomena.
Highlights
An effort of years covering more than 400 works of science and an order of magnitude more via machine learning: "Complexity Heliophysics: A Lived and Living History of Systems and Complexity Science in Heliophysics"
https://lnkd.in/eTB774Qu
🔥 Online today (open access!) in Space Science Reviews! #NASATOPS
Written to be a guiding document for the future of complexity science and AI, the work is a sweeping review of the lived and living history of complexity science as a paradigm of scientific discovery in Earth and space science.
It arrives at three pathways central to the future of the complexity science paradigm of scientific discovery, and thus to breakthrough discovery in Earth and space science: 1) Complexity – AI: understanding the connections between complexity science and machine learning/artificial intelligence; 2) Risk science and resilience: A ‘risk science’ framework can be a layer where fundamental understanding and predictive capability converge; and 3) Cultural challenges: interdisciplinary work requires new capacities for facilitation and team composition as well as new capabilities for integrating information, which together require new ways of ‘looking’ at a community (e.g., indicators and metrics).
NASA - National Aeronautics and Space Administration NASA Jet Propulsion Laboratory Santa Fe Institute #complexity #heliophysics #earthscience #spacesciencereviews #riskscience
