HelioWebMeng Jin
flowchart
A[Meng Jin]
AC["Associated Concepts (24)"]
AW["Authored Works (10)"]
CA["Linked Co-Authors (21)"]
CI["Linked Collaborating Institutions (26)"]
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AW== author ==>A
AW== author ==>CA
AW== affil ==>CI
click AC "#associated-concepts"
click AW "#authored-works"
click CA "#co-authors"
click CI "#collaborating-institutions"
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- ORCiD
- https://orcid.org/0000-0002-9672-3873
- OpenAlex ID
- https://openalex.org/A5084420818 (API record)
Associated Concepts [?]
- Physics
- Quantum mechanics
- Astronomy
- Astrophysics
- Biology
- Nuclear physics
- Magnetic field
- Plasma
- Geology
- Computer science
- Geography
- Solar wind
- Astrobiology
- Engineering
- Meteorology
- Coronal mass ejection
- Optics
- Mathematics
- Materials science
- Computer vision
- Aerospace engineering
- Thermodynamics
- Venus
- Environmental science
Authored Works
sorted by decreasing year, and then by display-name
- Living With the Young Sun: First Results of HST-XMM Newton and TESS Coordinated Observations of Young Suns and Modeling of Their Coronae, Winds and Eruptive Events
- Integrated and Interpretable Solar Flare Forecast with AIA and HMI Imaging Data: Application of the Spatial Transformer and Bayesian Neural Network
- Analysis of Flare/CME-Generated Quasi-Periodic Fast-Mode Wave Trains Observed by SDO/AIA
- Understanding the Origin of Fe-rich Gradual Solar Energetic Particle Events
- Stellar Coronal Magnetic Field Measurements Based on the Magnetic-field-induced Transition Theory
- Self-supervised Deep Learning for Reducing Data Transmission Needs in Multi-Wavelength Space Instruments: a case study based on the Solar Dynamics Observatory.
- Probing the Physics of the Solar Atmosphere with the Multi-slit Solar Explorer (MUSE): II. Flares and Eruptions
- Magnetic Life of Young Suns: Data Constrained Model of the Corona and Wind from k1 Ceti
- Extreme Energetic Particle Events by Superflare Associated CMEs from Planet Hosting Stars
- Beyond reproducibility at the Frontier Development Lab (FDL): Community driven continuous optimization for the SDO machine learning dataset (SDOML).
Linked Co-Authors
- Atılım Güneş Baydin
- Bart De Pontieu
- C. M. S. Cohen
- E. E. DeLuca
- G. P. Zank
- Gang Li
- Ignacio Ugarte-Urra
- L. F. Guedes dos Santos
- L. Golub
- M. Guêdel
- Marc L. DeRosa
- Miho Janvier
- N. Nitta
- P. Wright
- Paola Testa
- Suchismita Bose
- Tongjiang Wang
- V. H. Hansteen
- Wenxian Li
- Xudong Sun
- Yang Chen
Linked Collaborating Institutions
- Bay Area Environmental Research Institute, California
- California Institute of Technology
- Fudan University, China
- Institut d'Astrophysique Spatiale
- Lockheed Martin, Palo Alto
- Montana State University, Bozeman
- NASA Goddard Space Flight Center, Maryland
- National Center for Atmospheric Research, Colorado
- National Solar Observatory, Sunspot New Mexico
- Northumbria University, UK
- Osaka University, Japan
- Peking University, China
- SETI Institute, California
- Space Telescope Science Institute, Baltimore, Maryland
- Stanford University, California
- Stockholm University
- Swedish University of Agricultural Sciences
- University of Alabama, Huntsville
- University of Colorado, Boulder, Laboratory for Atmospheric and Space Physics
- University of Glasgow, UK
- University of Hawaii, Manoa
- University of Michigan
- University of Oslo, Institute of Theoretical Astrophysics
- University of Oslo, Norway
- University of Oxford, UK
- University of Vienna, Austria
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