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Hyunju Connor
NASA Goddard Space Flight CenterMeeting roles in:
Multiscale Physics of Magnetic Reconnection: Advances in Observations, Experiments, Modeling, and Theory I Oral
A Machine Learning-based Model of the Terrestrial Exospheric Emission Using Lyman-Alpha Radiance Data Acquired by NASA's TWINS Mission
Three-dimensional reconstruction of the terrestrial exospheric H density distributions using images acquired at the Lagrangian point 1 and a statistical approach.
Simulated Impacts of NO Cooling on Exospheric Hydrogen Using the Gravity-Only MATE Model
The KInetic-based Terrestrial Exospheric (KITE) model
Real-time forecasting model of auroral electron precipitation using AI techniques
Maryland Space Weather UnderGround Research and Outreach Program: Pushing the Boundaries of Next-Generation Low-Cost Ground Magnetometers
Multiscale Physics of Magnetic Reconnection: Advances in Observations, Experiments, Modeling, and Theory II Oral
Automatic Identification of Auroral Beads and Omega Bands in THEMIS All-Sky Images
TRACERS twin-spacecraft mission to resolve spatiotemporal variations of the ionosphere and upper thermosphere during CME-driven storms
Exospheric Impact on Earth’s Magnetosphere-Ionosphere-Thermosphere System
Multiscale Physics of Magnetic Reconnection: Advances in Observations, Experiments, Modeling, and Theory III Poster
A New X-line Model: Comparison to MHD Magnetic Separator
The TRACERS Small Explorers Mission
Tracing the Subsolar Magnetopause in Simulated SMILE Soft X-ray Images
Storm-Time Coupling Across the Upper Atmosphere, Exosphere, and Ring Current
Advancing Modeling of Magnetosphere-Ionosphere Coupling with the Enhanced OpenGGCM-GITM Framework
OpenGGCM's Coupling Framework and its Postprocessing and Visualization Library ggcmpy
The May 2024 Storm: dayside magnetopause and cusps in simulated soft X-Rays
Magnetic Reconnection Research: Challenges, Breakthroughs, and Future Missions
Harnessing AI for Geospace Science and Space Weather: The AIMFAHR Project
Predicting The Plasma Density In The Magnetosheath Using Machine Learning
Using Machine Learning Explainability Techniques to Examine Drivers of Ground Magnetic Field Localization
Implementation of a Regression Model for Ion Fluxes in the Low-Altitude Earth's Northern Cusp Using In-Situ DMSP/SSJ Data and a Residual Neural Network
Evaluating Auroral Boundary Predictions Using Machine Learning–Based Particle Precipitation Model
Utilizing Machine Learning to Predict High-Latitude Ionospheric Electrodynamics
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