Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Pegasus, a workflow management system for science automation
This map shows the geographic impact of S. Callaghan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. Callaghan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Callaghan more than expected).
This network shows the impact of papers produced by S. Callaghan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. Callaghan. The network helps show where S. Callaghan may publish in the future.
Co-authorship network of co-authors of S. Callaghan
This figure shows the co-authorship network connecting the top 25 collaborators of S. Callaghan.
A scholar is included among the top collaborators of S. Callaghan based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with S. Callaghan. S. Callaghan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Milner, Kevin R., S. Callaghan, P. J. Maechling, et al.. (2018). A SCEC CyberShake Physics-Based Probabilistic Seismic Hazard Model for Northern California. AGU Fall Meeting Abstracts. 2018.1 indexed citations
9.
Callaghan, S., P. J. Maechling, Christine Goulet, et al.. (2017). CyberShake Physics-Based PSHA in Central California. AGU Fall Meeting Abstracts. 2017.1 indexed citations
10.
Callaghan, S., P. J. Maechling, Christine Goulet, et al.. (2016). Expanding CyberShake Physics-Based Seismic Hazard Calculations to Central California. AGUFM. 2016.1 indexed citations
11.
Callaghan, S., et al.. (2015). Using CyberShake Workflows to Manage Big Seismic Hazard Data on Large-Scale Open-Science HPC Resources. 2015 AGU Fall Meeting. 2015.1 indexed citations
12.
Goulet, Christine, Ferran Silva, P. J. Maechling, S. Callaghan, & T. H. Jordan. (2015). The SCEC Broadband Platform: Open-Source Software for Strong Ground Motion Simulation and Validation. AGU Fall Meeting Abstracts. 2015.1 indexed citations
13.
Callaghan, S., et al.. (2014). Optimizing CyberShake Seismic Hazard Workflows for Large HPC Resources. 2014 AGU Fall Meeting. 2014.1 indexed citations
14.
Deelman, Ewa, Karan Vahi, Gideon Juve, et al.. (2014). Pegasus, a workflow management system for science automation. Future Generation Computer Systems. 46. 17–35.517 indexed citations breakdown →
15.
Jordán, Tibor, et al.. (2013). Using the Averaging-Based Factorization to Assess CyberShake Hazard Models. AGU Fall Meeting Abstracts. 2013.3 indexed citations
Katz, Daniel S., S. Callaghan, Robert P. Harkness, et al.. (2010). Science on the TeraGrid. Computational Methods in Science and Technology. Special Issue(1). 81–97.3 indexed citations
18.
Callaghan, S., P. J. Maechling, Robert Graves, et al.. (2010). Running On-Demand Strong Ground Motion Simulations with the Second-Generation Broadband Platform. AGU Fall Meeting Abstracts. 2010.1 indexed citations
19.
Maechling, P. J., T. H. Jordan, M. Liukis, & S. Callaghan. (2009). Developing Performance Measures for the CISN Earthquake Early Warning Testing Center. AGU Fall Meeting Abstracts. 2009.1 indexed citations
20.
Callaghan, S., Ewa Deelman, Dan Gunter, et al.. (2009). Scaling up workflow-based applications. Journal of Computer and System Sciences. 76(6). 428–446.41 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.