Mark Jessell

8.3k total citations
203 papers, 5.5k citations indexed

About

Mark Jessell is a scholar working on Geophysics, Artificial Intelligence and Geochemistry and Petrology. According to data from OpenAlex, Mark Jessell has authored 203 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 129 papers in Geophysics, 68 papers in Artificial Intelligence and 66 papers in Geochemistry and Petrology. Recurrent topics in Mark Jessell's work include Geochemistry and Geologic Mapping (67 papers), Geological Modeling and Analysis (65 papers) and Geological and Geochemical Analysis (60 papers). Mark Jessell is often cited by papers focused on Geochemistry and Geologic Mapping (67 papers), Geological Modeling and Analysis (65 papers) and Geological and Geochemical Analysis (60 papers). Mark Jessell collaborates with scholars based in Australia, France and United States. Mark Jessell's co-authors include Paul D. Bons, Mark Lindsay, Lenka Baratoux, Laurent Aillères, Gordon Lister, Jérémie Giraud, Vitaliy Ogarko, Séta Naba, Jérôme Ganne and Václav Metelka and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Remote Sensing of Environment.

In The Last Decade

Mark Jessell

198 papers receiving 5.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Jessell Australia 46 3.7k 1.9k 1.5k 822 594 203 5.5k
James K. Russell Canada 42 5.5k 1.5× 1.3k 0.7× 417 0.3× 599 0.7× 257 0.4× 197 6.8k
Guoqiang Tang China 35 3.2k 0.9× 1.2k 0.7× 551 0.4× 136 0.2× 339 0.6× 140 5.3k
Cees W. Passchier Germany 46 5.6k 1.5× 1.1k 0.6× 283 0.2× 1.1k 1.3× 252 0.4× 168 6.9k
Paul D. Bons Germany 43 3.7k 1.0× 855 0.5× 259 0.2× 1.7k 2.0× 343 0.6× 195 5.9k
B. E. Hobbs Australia 48 5.5k 1.5× 1.2k 0.7× 364 0.2× 2.5k 3.1× 668 1.1× 257 9.1k
R. E. Holdsworth United Kingdom 56 7.7k 2.1× 1.3k 0.7× 431 0.3× 1.3k 1.6× 268 0.5× 217 9.1k
Alison Ord Australia 45 3.3k 0.9× 1.1k 0.6× 331 0.2× 1.9k 2.3× 565 1.0× 214 6.2k
Yury Podladchikov Switzerland 49 6.0k 1.6× 493 0.3× 278 0.2× 1.7k 2.0× 617 1.0× 211 8.0k
Guido Ventura Italy 42 4.3k 1.2× 689 0.4× 326 0.2× 379 0.5× 229 0.4× 179 5.9k
Zoe K. Shipton United Kingdom 31 3.3k 0.9× 492 0.3× 338 0.2× 1.5k 1.9× 722 1.2× 105 5.1k

Countries citing papers authored by Mark Jessell

Since Specialization
Citations

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

Fields of papers citing papers by Mark Jessell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Jessell

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Jessell. A scholar is included among the top collaborators of Mark Jessell 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 Mark Jessell. Mark Jessell 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.
Jessell, Mark, et al.. (2024). An open-source, QGIS-based solution for digital geological mapping: GEOL-QMAPS. SHILAP Revista de lepidopterología. 24. 100197–100197. 1 indexed citations
2.
Ogarko, Vitaliy, et al.. (2024). Tomofast-x 2.0: an open-source parallel code for inversion of potential field data with topography using wavelet compression. Geoscientific model development. 17(6). 2325–2345. 3 indexed citations
3.
Guo, Jiateng, Luyuan Wang, Lixin Wu, et al.. (2024). GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data. Geoscientific model development. 17(3). 957–973. 9 indexed citations
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Jessell, Mark, Jiateng Guo, Yunqiang Li, et al.. (2022). Into the Noddyverse: a massive data store of 3D geological models for machine learning and inversion applications. Earth system science data. 14(1). 381–392. 24 indexed citations
7.
Giraud, Jérémie, Vitaliy Ogarko, Roland Martin, Mark Jessell, & Mark Lindsay. (2021). Structural, petrophysical, and geological constraints in potential field inversion using the Tomofast-x v1.0 open-source code. Geoscientific model development. 14(11). 6681–6709. 20 indexed citations
8.
Jessell, Mark, Vitaliy Ogarko, Mark Lindsay, et al.. (2021). Automated geological map deconstruction for 3D model construction. 5 indexed citations
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Jessell, Mark, Vitaliy Ogarko, Mark Lindsay, et al.. (2021). Automated geological map deconstruction for 3D model construction using map2loop 1.0 and map2model 1.0. Geoscientific model development. 14(8). 5063–5092. 22 indexed citations
11.
Jessell, Mark, Jiateng Guo, Yunqiang Li, et al.. (2021). Into the Noddyverse: A massive data store of 3D geological models for Machine Learning & inversion applications. 1 indexed citations
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Giraud, Jérémie, Mark Lindsay, Mark Jessell, & Vitaliy Ogarko. (2020). Towards plausible lithological classification from geophysical inversion: honouring geological principles in subsurface imaging. Solid Earth. 11(2). 419–436. 20 indexed citations
14.
Ogarko, Vitaliy, Jérémie Giraud, Roland Martin, & Mark Jessell. (2020). Disjoint interval bound constraints using the alternating direction method of multipliers for geologically constrained inversion: Application to gravity data. Geophysics. 86(2). G1–G11. 23 indexed citations
15.
Giraud, Jérémie, Mark Lindsay, Mark Jessell, & Vitaliy Ogarko. (2019). Towards geologically reasonable lithological classification from integrated geophysical inverse modelling: methodology and application case. 2 indexed citations
16.
Pakyuz-Charrier, Evren, Mark Jessell, Jérémie Giraud, Mark Lindsay, & Vitaliy Ogarko. (2019). Topological analysis in Monte Carlo simulation for uncertainty propagation. Solid Earth. 10(5). 1663–1684. 24 indexed citations
17.
Pakyuz-Charrier, Evren, Mark Lindsay, Vitaliy Ogarko, Jérémie Giraud, & Mark Jessell. (2018). Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization. Solid Earth. 9(2). 385–402. 70 indexed citations
18.
Giraud, Jérémie, Evren Pakyuz-Charrier, Mark Jessell, et al.. (2017). Uncertainty reduction through geologically conditioned petrophysical constraints in joint inversion. Geophysics. 82(6). ID19–ID34. 52 indexed citations
19.
Pakyuz-Charrier, Evren, Mark Lindsay, Vitaliy Ogarko, Jérémie Giraud, & Mark Jessell. (2017). Monte Carlo Simulations for Uncertainty Estimation in 3D Geological Modeling, A Guide for Disturbance Distribution Selection and Parameterization. UWA Profiles and Research Repository (University of Western Australia). 2 indexed citations
20.
Lindsay, Mark, Stéphane Perrouty, Mark Jessell, et al.. (2011). Categorising features of geological terranes with geodiversity metrics: Enhancing exploration of multiple geological models. Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation.. 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.

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