Niklas W. A. Gebauer

447 total citations
5 papers, 221 citations indexed

About

Niklas W. A. Gebauer is a scholar working on Materials Chemistry, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Niklas W. A. Gebauer has authored 5 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Materials Chemistry, 3 papers in Molecular Biology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Niklas W. A. Gebauer's work include Machine Learning in Materials Science (5 papers), Protein Structure and Dynamics (2 papers) and Computational Drug Discovery Methods (2 papers). Niklas W. A. Gebauer is often cited by papers focused on Machine Learning in Materials Science (5 papers), Protein Structure and Dynamics (2 papers) and Computational Drug Discovery Methods (2 papers). Niklas W. A. Gebauer collaborates with scholars based in Germany, United States and South Korea. Niklas W. A. Gebauer's co-authors include Michael Gastegger, Kristof T. Schütt, Klaus‐Robert Müller, Jonas Lederer, Rajendra P. Joshi, Neeraj Kumar, James Brown, Tamio Oguchi and Tomoki Yamashita and has published in prestigious journals such as Nature Communications, The Journal of Chemical Physics and The Journal of Physical Chemistry B.

In The Last Decade

Niklas W. A. Gebauer

5 papers receiving 211 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Niklas W. A. Gebauer Germany	5	155	124	70	24	21	5	221
Yuanqing Wang United States	9	160 1.0×	106 0.9×	119 1.7×	17 0.7×	10 0.5×	15	256
Marius Kühnemund Germany	4	238 1.5×	173 1.4×	72 1.0×	18 0.8×	23 1.1×	4	339
Donglong He China	3	243 1.6×	279 2.3×	191 2.7×	13 0.5×	51 2.4×	3	384
Youngchun Kwon South Korea	12	279 1.8×	257 2.1×	201 2.9×	36 1.5×	37 1.8×	15	459
Clemens Isert Switzerland	8	188 1.2×	242 2.0×	186 2.7×	10 0.4×	17 0.8×	12	336
Benoît Baillif France	3	129 0.8×	190 1.5×	168 2.4×	33 1.4×	15 0.7×	4	330
Geemi P. Wellawatte United States	7	165 1.1×	116 0.9×	78 1.1×	15 0.6×	63 3.0×	8	253
Seongok Ryu South Korea	6	204 1.3×	295 2.4×	253 3.6×	26 1.1×	44 2.1×	9	428
Samuel Goldman United States	9	134 0.9×	148 1.2×	170 2.4×	12 0.5×	35 1.7×	12	379
Daniel Wigh United Kingdom	3	158 1.0×	159 1.3×	90 1.3×	18 0.8×	18 0.9×	5	288

Countries citing papers authored by Niklas W. A. Gebauer

Since Specialization

Citations

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

Fields of papers citing papers by Niklas W. A. Gebauer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Niklas W. A. Gebauer. 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 Niklas W. A. Gebauer. The network helps show where Niklas W. A. Gebauer may publish in the future.

Co-authorship network of co-authors of Niklas W. A. Gebauer

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

All Works

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5 of 5 papers shown

1.

Schütt, Kristof T., et al.. (2025). Accelerating crystal structure search through active learning with neural networks for rapid relaxations. npj Computational Materials. 11(1). 6 indexed citations

2.

Schütt, Kristof T., et al.. (2023). SchNetPack 2.0: A neural network toolbox for atomistic machine learning. The Journal of Chemical Physics. 158(14). 144801–144801. 55 indexed citations

3.

Gebauer, Niklas W. A., et al.. (2022). Inverse design of 3d molecular structures with conditional generative neural networks. Nature Communications. 13(1). 973–973. 123 indexed citations

4.

Joshi, Rajendra P., et al.. (2021). 3D-Scaffold: A Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds. The Journal of Physical Chemistry B. 125(44). 12166–12176. 31 indexed citations

5.

Gebauer, Niklas W. A., Michael Gastegger, & Kristof T. Schütt. (2019). Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules. arXiv (Cornell University). 32. 7564–7576. 6 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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