Jesper Dramsch

725 total citations · 1 hit paper
17 papers, 347 citations indexed

About

Jesper Dramsch is a scholar working on Geophysics, Ocean Engineering and Artificial Intelligence. According to data from OpenAlex, Jesper Dramsch has authored 17 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Geophysics, 8 papers in Ocean Engineering and 8 papers in Artificial Intelligence. Recurrent topics in Jesper Dramsch's work include Seismic Imaging and Inversion Techniques (10 papers), Reservoir Engineering and Simulation Methods (7 papers) and Hydraulic Fracturing and Reservoir Analysis (6 papers). Jesper Dramsch is often cited by papers focused on Seismic Imaging and Inversion Techniques (10 papers), Reservoir Engineering and Simulation Methods (7 papers) and Hydraulic Fracturing and Reservoir Analysis (6 papers). Jesper Dramsch collaborates with scholars based in Denmark, United Kingdom and United States. Jesper Dramsch's co-authors include Mikael Lüthje, Thomas Mejer Hansen, Runhai Feng, Darío Graña, Niels Balling, Anders Nymark Christensen, Colin MacBeth, Lukas Mosser, Mariana Clare and Zied Ben Bouallègue and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Nature Geoscience and Bulletin of the American Meteorological Society.

In The Last Decade

Jesper Dramsch

17 papers receiving 335 citations

Hit Papers

The Rise of Data-Driven W... 2024 2026 2024 20 40 60
What are hit papers?

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.

  1. The Rise of Data-Driven Weather Forecasting: A First Statistical Assessment of Machine Learning–Based Weather Forecasts in an Operational-Like Context
    2024 70 citations Zied Ben Bouallègue, Mariana Clare et al. Bulletin of the American Meteorological Society profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jesper Dramsch 168 140 78 73 65 17 347
Zhongping Zhang 166 1.0× 97 0.7× 82 1.1× 47 0.6× 214 3.3× 22 482
Anton A. Duchkov 285 1.7× 134 1.0× 39 0.5× 89 1.2× 23 0.4× 88 490
Yang Su 205 1.2× 135 1.0× 28 0.4× 30 0.4× 40 0.6× 48 336
Sheng Zhang 421 2.5× 259 1.9× 88 1.1× 97 1.3× 26 0.4× 77 725
Siwei Li 149 0.9× 85 0.6× 16 0.2× 42 0.6× 94 1.4× 24 312
Heidi Anderson Kuzma 220 1.3× 177 1.3× 42 0.5× 71 1.0× 19 0.3× 24 328
SanLinn I. Kaka 433 2.6× 116 0.8× 145 1.9× 66 0.9× 9 0.1× 60 664
Hai Li 494 2.9× 367 2.6× 97 1.2× 42 0.6× 27 0.4× 58 636
Vikram Jayaram 241 1.4× 247 1.8× 85 1.1× 209 2.9× 13 0.2× 31 439
Franklin G. Horowitz 323 1.9× 100 0.7× 88 1.1× 33 0.5× 15 0.2× 11 548

Countries citing papers authored by Jesper Dramsch

Since Specialization
Citations

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

Fields of papers citing papers by Jesper Dramsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jesper Dramsch

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

All Works

17 of 17 papers shown
1.
Dramsch, Jesper, Miguel‐Ángel Fernández‐Torres, Andrea Toreti, et al.. (2025). Explainability can foster trust in artificial intelligence in geoscience. Nature Geoscience. 18(2). 112–114. 14 indexed citations
2.
Nipen, Thomas N., Ivar A. Seierstad, Jørn Kristiansen, et al.. (2025). Regional data-driven weather modeling with a global stretched-grid. 2 indexed citations
3.
Bouallègue, Zied Ben, Mariana Clare, Linus Magnusson, et al.. (2024). The Rise of Data-Driven Weather Forecasting: A First Statistical Assessment of Machine Learning–Based Weather Forecasts in an Operational-Like Context. Bulletin of the American Meteorological Society. 105(6). E864–E883. 70 indexed citations breakdown →
4.
Bouallègue, Zied Ben, Jonathan A. Weyn, Mariana Clare, et al.. (2023). Improving Medium-Range Ensemble Weather Forecasts with Hierarchical Ensemble Transformers. 3(1). 15 indexed citations
5.
Feng, Runhai, Niels Balling, Darío Graña, Jesper Dramsch, & Thomas Mejer Hansen. (2021). Bayesian Convolutional Neural Networks for Seismic Facies Classification. IEEE Transactions on Geoscience and Remote Sensing. 59(10). 8933–8940. 66 indexed citations
6.
Dramsch, Jesper, Anders Nymark Christensen, Colin MacBeth, & Mikael Lüthje. (2021). Deep Unsupervised 4-D Seismic 3-D Time-Shift Estimation With Convolutional Neural Networks. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–16. 9 indexed citations
7.
8.
Dramsch, Jesper, et al.. (2020). Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets. Geophysical Prospecting. 68(7). 2164–2185. 18 indexed citations
9.
Dramsch, Jesper, Mikael Lüthje, & Anders Nymark Christensen. (2020). Complex-valued neural networks for machine learning on non-stationary physical data. Computers & Geosciences. 146. 104643–104643. 25 indexed citations
10.
Dramsch, Jesper. (2020). Machine Learning in Geoscience Applications of Deep Neural Networks in 4D Seismic Data Analysis. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 3 indexed citations
11.
Dramsch, Jesper, et al.. (2019). An integrated workflow for fracture characterization in chalk reservoirs, applied to the Kraka Field. Marine and Petroleum Geology. 112. 104065–104065. 6 indexed citations
12.
13.
Dramsch, Jesper. (2019). Machine Learning in 4D Seismic Data Analysis: Deep Neural Networks in Geophysics. 1 indexed citations
14.
Dramsch, Jesper & Mikael Lüthje. (2018). Deep-learning seismic facies on state-of-the-art CNN architectures. 2036–2040. 67 indexed citations
15.
Dramsch, Jesper, Frédéric Amour, & Mikael Lüthje. (2018). Gaussian Mixture Models For Robust Unsupervised Scanning-Electron Microscopy Image Segmentation Of North Sea Chalk. Proceedings. 1 indexed citations
16.
Dramsch, Jesper & Mikael Lüthje. (2018). Information Theory Considerations In Patch-Based Training Of Deep Neural Networks On Seismic Time-Series. Proceedings. 1 indexed citations
17.

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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