Dan Hollis

1.4k total citations · 1 hit paper
28 papers, 981 citations indexed

About

Dan Hollis is a scholar working on Geophysics, Artificial Intelligence and Ocean Engineering. According to data from OpenAlex, Dan Hollis has authored 28 papers receiving a total of 981 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Geophysics, 14 papers in Artificial Intelligence and 7 papers in Ocean Engineering. Recurrent topics in Dan Hollis's work include Seismic Waves and Analysis (21 papers), Seismology and Earthquake Studies (14 papers) and Seismic Imaging and Inversion Techniques (13 papers). Dan Hollis is often cited by papers focused on Seismic Waves and Analysis (21 papers), Seismology and Earthquake Studies (14 papers) and Seismic Imaging and Inversion Techniques (13 papers). Dan Hollis collaborates with scholars based in France, United States and United Kingdom. Dan Hollis's co-authors include Dunzhu Li, Fan‐Chi Lin, Robert W. Clayton, Mark McCarthy, Michael Kendon, I. Simpson, Tim Legg, Zefeng Li, Zhigang Peng and James H. McClellan and has published in prestigious journals such as Scientific Reports, Geophysical Research Letters and Ecology Letters.

In The Last Decade

Dan Hollis

25 papers receiving 959 citations

Hit Papers

High-resolution 3D shallow crustal structure in Long Beac... 2013 2026 2017 2021 2013 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dan Hollis France 11 685 319 170 126 86 28 981
Josodhir Das India 17 332 0.5× 153 0.5× 70 0.4× 141 1.1× 110 1.3× 43 726
Mohammad Reza Saradjian Iran 16 249 0.4× 133 0.4× 71 0.4× 153 1.2× 182 2.1× 54 723
Sylvester K. Danuor Ghana 15 215 0.3× 111 0.3× 100 0.6× 120 1.0× 201 2.3× 46 584
Duncan Hay United Kingdom 11 286 0.4× 133 0.4× 33 0.2× 37 0.3× 33 0.4× 38 563
Roger A. Clark United Kingdom 19 908 1.3× 55 0.2× 532 3.1× 6 0.0× 241 2.8× 67 1.3k
Àlex Martínez United States 11 347 0.5× 30 0.1× 287 1.7× 39 0.3× 31 0.4× 32 539
Velio Coviello Italy 16 238 0.3× 106 0.3× 30 0.2× 222 1.8× 161 1.9× 49 728
Muhammad Younis Khan Pakistan 14 248 0.4× 35 0.1× 204 1.2× 47 0.4× 12 0.1× 42 456
D. Oertel Germany 14 40 0.1× 54 0.2× 126 0.7× 380 3.0× 234 2.7× 63 1.0k
Johannes Schmidt Germany 12 56 0.1× 37 0.1× 46 0.3× 38 0.3× 127 1.5× 40 463

Countries citing papers authored by Dan Hollis

Since Specialization
Citations

This map shows the geographic impact of Dan Hollis'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 Dan Hollis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Hollis more than expected).

Fields of papers citing papers by Dan Hollis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dan Hollis. 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 Dan Hollis. The network helps show where Dan Hollis may publish in the future.

Co-authorship network of co-authors of Dan Hollis

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Hollis. A scholar is included among the top collaborators of Dan Hollis 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 Dan Hollis. Dan Hollis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kendon, Mike, Dan Hollis, Emily Carlisle, et al.. (2025). State of the UK Climate in 2024. International Journal of Climatology. 45(S1).
2.
Kendon, Mike, Dan Hollis, Emily Carlisle, et al.. (2024). State of the UK Climate 2023. International Journal of Climatology. 44(S1). 1–117. 11 indexed citations
3.
Sheng, Yixiao, Aurélien Mordret, Florent Brenguier, et al.. (2024). Body waves from train noise correlations: potential and limits for monitoring the San Jacinto Fault, CA. Geophysical Journal International. 240(1). 721–729. 1 indexed citations
4.
Sheng, Yixiao, Aurélien Mordret, Florent Brenguier, et al.. (2024). Tracking Seismic Velocity Perturbations at Ridgecrest Using Ballistic Correlation Functions. Seismological Research Letters. 95(4). 2452–2463. 4 indexed citations
5.
Sheng, Yixiao, Florent Brenguier, Aurélien Mordret, et al.. (2024). In Situ Velocity‐Strain Sensitivity Near the San Jacinto Fault Zone Analyzed Through Train Tremors. Geophysical Research Letters. 51(15). 3 indexed citations
6.
Naghizadeh, Mostafa, Richard S. Smith, Ross Sherlock, et al.. (2022). Active and Passive Seismic Imaging of the Central Abitibi Greenstone Belt, Larder Lake, Ontario. Journal of Geophysical Research Solid Earth. 127(2). 1 indexed citations
7.
Chadwick, David R., Ian Harris, A. Hines, et al.. (2020). Spatial co‐localisation of extreme weather events: a clear and present danger. Ecology Letters. 24(1). 60–72. 15 indexed citations
8.
Arndt, Nicholas, John H. McBride, Aurélien Mordret, et al.. (2020). Ambient Noise Rayleigh and Love Wave Tomography beneath the Sally Palladium Copper Deposit (Ontario, Canada). 1–5. 1 indexed citations
9.
Hollis, Dan, Mark McCarthy, Michael Kendon, Tim Legg, & I. Simpson. (2019). HadUK‐Grid—A new UK dataset of gridded climate observations. Geoscience Data Journal. 6(2). 151–159. 200 indexed citations
10.
Chmiel, Małgorzata, Aurélien Mordret, Pierre Boué, et al.. (2019). Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field. Geophysical Journal International. 218(3). 1781–1795. 45 indexed citations
11.
Hollis, Dan, John H. McBride, David Good, et al.. (2018). Use of ambient-noise surface-wave tomography in mineral resource exploration and evaluation. 1937–1940. 16 indexed citations
12.
Roux, Philippe, Dino Bindi, Tobias Boxberger, et al.. (2018). Toward Seismic Metamaterials: The METAFORET Project. Seismological Research Letters. 89(2A). 582–593. 41 indexed citations
13.
Li, Zefeng, et al.. (2018). High-resolution seismic event detection using local similarity for Large-N arrays. Scientific Reports. 8(1). 1646–1646. 93 indexed citations
14.
Mateeva, Albena, et al.. (2016). Introduction to this special section: Advances in seismic sensors. The Leading Edge. 35(7). 574–576.
15.
Sumy, D. F., et al.. (2015). Sweetwater, Texas Large N Experiment. 2015 AGU Fall Meeting. 2015. 1 indexed citations
16.
Li, Zefeng, Zhigang Peng, Xiaofeng Meng, et al.. (2015). Matched Filter Detection of Microseismicity in Long Beach with a 5200-station Dense Array. 118. 2615–2619. 7 indexed citations
17.
Ben‐Zion, Yehuda, F. L. Vernon, Dimitri Zigone, et al.. (2015). Basic data features and results from a spatially dense seismic array on the San Jacinto fault zone. Geophysical Journal International. 202(1). 370–380. 123 indexed citations
18.
Hollis, Dan, et al.. (2014). A Large-N Mixed Sensor Active + Passive Seismic Array near Sweetwater, TX. 2014 AGU Fall Meeting. 2014.
19.
Kendon, Mike & Dan Hollis. (2014). How are UK rainfall‐anomaly statistics calculated and does it matter?. Weather. 69(2). 37–39. 8 indexed citations
20.
Lin, Fan‐Chi, Dunzhu Li, Robert W. Clayton, & Dan Hollis. (2013). High-resolution 3D shallow crustal structure in Long Beach, California: Application of ambient noise tomography on a dense seismic array. Geophysics. 78(4). Q45–Q56. 351 indexed citations breakdown →

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.

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