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.
P Wave Arrival Picking and First‐Motion Polarity Determination With Deep Learning
2018378 citationsZachary E. Ross, Men‐Andrin Meier et al.Journal of Geophysical Research Solid Earthprofile →
Generalized Seismic Phase Detection with Deep Learning
2018347 citationsZachary E. Ross, Men‐Andrin Meier et al.Bulletin of the Seismological Society of Americaprofile →
Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence
2019346 citationsZachary E. Ross, Benjamín Idini et al.Scienceprofile →
Machine Learning in Seismology: Turning Data into Insights
2018346 citationsDaniel T. Trugman, Zachary E. Ross et al.profile →
Searching for hidden earthquakes in Southern California
2019252 citationsZachary E. Ross, Daniel T. Trugman et al.Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Zachary E. Ross
Since
Specialization
Citations
This map shows the geographic impact of Zachary E. Ross'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 Zachary E. Ross with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zachary E. Ross more than expected).
This network shows the impact of papers produced by Zachary E. Ross. 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 Zachary E. Ross. The network helps show where Zachary E. Ross may publish in the future.
Co-authorship network of co-authors of Zachary E. Ross
This figure shows the co-authorship network connecting the top 25 collaborators of Zachary E. Ross.
A scholar is included among the top collaborators of Zachary E. Ross 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 Zachary E. Ross. Zachary E. Ross is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Castellanos, Jorge C., et al.. (2021). DeepGEM: Generalized Expectation-Maximization for Blind Inversion. CaltechAUTHORS (California Institute of Technology). 34.2 indexed citations
Ross, Zachary E., et al.. (2019). A focal mechanism catalog for Southern California derived with deep learning algorithms. AGU Fall Meeting Abstracts. 2019.1 indexed citations
Hauksson, Egill, Zachary E. Ross, Joann M. Stock, Men‐Andrin Meier, & E. S. Cochran. (2019). The 2019 M6.4 and M7.1 Ridgecrest Earthquake Sequence in the eastern California Shear Zone: Overview of Tectonic and Seismological Lessons. AGU Fall Meeting Abstracts. 2019.1 indexed citations
15.
Ross, Zachary E., Benjamín Idini, Zhe Jia, et al.. (2019). Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence. Science. 366(6463). 346–351.346 indexed citations breakdown →
16.
Ross, Zachary E., et al.. (2018). A Deep Learning Approach to Seismic Phase Association. AGU Fall Meeting Abstracts. 2018.1 indexed citations
Share, Pieter‐Ewald, et al.. (2015). Characterization of the San Jacinto Fault Zone Northwest of the Trifurcation Area from Earthquake Data Recorded by a Dense Linear Array. AGUFM. 2015.1 indexed citations
20.
Bohnhoff, Marco, et al.. (2014). Systematic imaging of bimaterial interfaces at the at the Karadere-Düzce segment of the North Anatolian Fault Zone, Turkey. 2014 AGU Fall Meeting. 2014.1 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.