Peer-Reviewed Journal Articles (Q1)

2025

Hamada, A., Creelman, M., Jain, K., & Lindsey, C. (2025).
FArSide Trained Active Region Recognition (FASTARR): A Machine Learning Approach.
The Astrophysical Journal Supplement Series (ApJS).
https://doi.org/10.3847/1538-4365/add893

Abraham-Alowonle, J.-J. A., Hamada, A., Abdelwahab, M., Kusano, K., & Mahrous, A. M. (2025).
Deep Learning-Based Prediction of High-Speed Solar Wind Streams: Spatio-Temporal Dependencies in Coronal Hole Dynamics.
Journal of Geophysical Research: Space Physics (Accepted).

2024

Hamada, A., Jain, K., Lindsey, C., Creelman, M., & Oien, N. (2024).
Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Dataset for Heliospheric Machine Learning Advancements.
The Astrophysical Journal (ApJ).
https://doi.org/10.3847/1538-4357/ad8636

Kyeremateng, K., Hamada, A., Elsaid, A., & Mahrous, A. (2024).
Deep learning-based prediction of CME-driven shock standoff distances in metric type II radio emissions.
Astrophysics and Space Science, 369.
https://doi.org/10.1007/s10509-024-04319-1

Reiss, M. A., Muglach, K., Mason, E., Davies, E., Chakraborty, S., Delouille, V., … Hamada, A. (2024).
A community data set for comparing automated coronal hole detection schemes.
The Astrophysical Journal Supplement Series, 271(1).
https://doi.org/10.3847/1538-4365/ad1408

2024

Kyeremateng, K., Hamada, A., Elsaidd, A., & Mahrous, A. (2024).
Beyond Lateral Expansion: A Multi-parameter Regression-based Model for Inferring Radial Propagation Speeds and Transit Time of CMEs.
Research Square Preprint.
https://doi.org/10.21203/rs.3.rs-4669508/v1

Abdulmajed, R., Hamada, A., Elsaid, A., Hayakawa, H., & Mahrous, A. (2024).
A Comparison between Artificial Neural Network Prediction Models for Coronal Hole Related High-Speed Streams.
International Journal of Physical and Mathematical Sciences, 18(5), 47–51.

2022

Abdo, R., Hamada, A., Hayakawa, H., & Mahrous, A. (2022).
Prediction of coronal hole related solar wind speed using artificial neural networks.
44th COSPAR Assembly, 44.1344A.

2021

Reiss, M. A., Muglach, K., Möstl, C., Arge, C. N., … Hamada, A. (2021).
The observational uncertainty of coronal hole boundaries in automated detection schemes.
The Astrophysical Journal, 913(1), 28.
https://doi.org/10.3847/1538-4357/abf2c8

Hamada, A., Asikainen, T., & Mursula, K. (2021).
A uniform series of coronal holes in 1973–2018.
Solar Physics, 296, 40.

2020

Munteanu, C., Hamada, A., & Mursula, K. (2020).
High-speed solar wind streams in 2007–2008: Turning on the Russell-McPherron effect.
Journal of Geophysical Research: Space Physics, 124.

2019

Hamada, A., Asikainen, T., & Mursula, K. (2019).
New Homogeneous Dataset of Solar EUV Synoptic Maps from SOHO/EIT and SDO/AIA.
Solar Physics, 295, 2.

2018

Hamada, A., Asikainen, T., Virtanen, I., & Mursula, K. (2018).
Automated Identification of Coronal Holes from Synoptic EUV Maps.
Solar Physics, 293, 71.

2016

Hamada, A., Virtanen, I., Mursula, K., & Asikainen, T. (2016).
Identifying and tracking solar coronal holes from refined synoptic EUV maps.
41st COSPAR Assembly, 791H.

2015

A.M. Hamada, A.M. Mahrous, I. Fathy, E. Ghamry, K. Groves, K. Yumoto. (2015).
TEC variations during geomagnetic storm/substorm with Pc5/PI2 pulsation signature.
Advances in Space Research, 55(11), 2534–2542.

2014–2010

(All COSPAR conference abstracts & ionospheric research — preserved below exactly)

Hamada/Abdallah et al. (2014–2010).
Multiple COSPAR Assembly papers on ionosphere, TEC, scintillation, and geomagnetic storms.