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Jamey Szalay
Princeton UniversityMeeting roles in:
Heavy Ions as Tracers and Regulators of Plasma Processes in the Solar System Poster
Temporal Variations of Jupiter's Plasma Disk Observed by Juno
A Forward Modeling Approach to Compton-Getting Corrections for IBEX Measurements
Dynamics of the Heliospheric Boundary Inferred from IBEX-Derived Line-of-Sight Pressures
Exploring the Outer Heliosphere through ENA observations from IMAP
The Interstellar Dust Experiment (IDEX) onboard the IMAP Mission: Performance and First-light Results
A Forward Modeling Approach to Compton-Getting Corrections for IBEX Measurements
Dynamics of the Heliospheric Boundary Inferred from IBEX-Derived Line-of-Sight Pressures
On the link between quasi-monoenergetic electron distributions and dispersive Alfvén waves in the Jovian and terrestrial magnetospheres
Investigating Field Line Resonances in the Jovian Plasma Sheet: Findings from Continuous Wavelet and Hilbert-Huang Transform Analysis of Juno Mission Data
The Dust Environment Near Jupiter
Measuring Olivine Elemental Ratios with Impact Ionization Dust Instruments
Utilizing IDEX in the hunt for organic cosmic dust grains
In situ observations of the topside polar ionosphere by Juno/JADE-I
Electron instabilities in the Jovian magnetodisc and implications for Alfvén wave excitation
A Quest of Understanding SEP Background in the Inner Heliosphere
Contribution of Solar Energetic Particles to the Total Pressure in the Inner Heliosphere
Non-Maxwellian, anisotropic electron distributions at Europa
Reconstructing Europa’s atmosphere from the Juno PJ45 flyby
Active Asteroids as a Possible Source of Meteoroid Streams Detected In-Situ in the Near-Sun Interplanetary Dust Cloud
What Drives Ion Outflow at Jupiter?
Sources, transport, and loss of pickup ions at Ganymede
Ion Composition and Spectral Properties in the Intense Solar Energetic Particle Events Observed by PSP/ISʘIS/EPI-Hi/LET
Out-of-the-Ecliptic Dust Investigation via Solar Orbiter RPW Observations
Reconstructing PSP/ISOIS Pitch Angle Resolved Intensities Using Machine Learning
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