Dominik Dold

415 total citations
12 papers, 115 citations indexed

About

Dominik Dold is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Dominik Dold has authored 12 papers receiving a total of 115 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Electrical and Electronic Engineering, 7 papers in Cognitive Neuroscience and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Dominik Dold's work include Advanced Memory and Neural Computing (9 papers), Neural dynamics and brain function (7 papers) and Ferroelectric and Negative Capacitance Devices (4 papers). Dominik Dold is often cited by papers focused on Advanced Memory and Neural Computing (9 papers), Neural dynamics and brain function (7 papers) and Ferroelectric and Negative Capacitance Devices (4 papers). Dominik Dold collaborates with scholars based in Netherlands, Germany and Switzerland. Dominik Dold's co-authors include Ákos F. Kungl, Mihai A. Petrovici, Karlheinz Meier, Oliver Breitwieser, Johannes Schemmel, Walter Senn, Laura Kriener, Benjamin Cramer, Sebastian Billaudelle and Marcel Hildebrandt and has published in prestigious journals such as eLife, Astronomy and Astrophysics and Neural Networks.

In The Last Decade

Dominik Dold

10 papers receiving 113 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dominik Dold Netherlands	4	92	59	46	24	5	12	115
Jakob Jordan Switzerland	7	114 1.2×	131 2.2×	33 0.7×	59 2.5×	2 0.4×	19	170
Guangzhi Tang Netherlands	7	146 1.6×	81 1.4×	53 1.2×	44 1.8×	2 0.4×	18	173
Adarsha Balaji United States	10	247 2.7×	46 0.8×	70 1.5×	76 3.2×	2 0.4×	14	263
Stefano Recanatesi United States	7	40 0.4×	128 2.2×	69 1.5×	42 1.8×	1 0.2×	12	168
Oliver Breitwieser Germany	7	164 1.8×	112 1.9×	70 1.5×	52 2.2×		9	183
Jens Bürger United States	5	102 1.1×	37 0.6×	36 0.8×	24 1.0×		12	115
Rajendra Bishnoi Netherlands	11	223 2.4×	27 0.5×	36 0.8×	51 2.1×	17 3.4×	25	247
Abhairaj Singh Netherlands	10	177 1.9×	14 0.2×	31 0.7×	42 1.8×	12 2.4×	16	196
Tommaso Salvatori United Kingdom	7	24 0.3×	52 0.9×	33 0.7×	17 0.7×	2 0.4×	13	96
Alessandro Milozzi Italy	5	153 1.7×	39 0.7×	25 0.5×	62 2.6×	19 3.8×	6	164

Countries citing papers authored by Dominik Dold

Since Specialization

Citations

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

Fields of papers citing papers by Dominik Dold

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dominik Dold

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

All Works

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12 of 12 papers shown

1.

Müller, E., et al.. (2025). Scalable network emulation on analog neuromorphic hardware. Frontiers in Neuroscience. 18. 1523331–1523331. 1 indexed citations

2.

Lunghi, Paolo, et al.. (2025). Energy efficiency analysis of Spiking Neural Networks for space applications. Astrodynamics. 9(6). 909–932.

3.

Dold, Dominik, et al.. (2025). Memristor-based neural network accelerators for space applications: Enhancing performance with temporal averaging and SIRENs. Acta Astronautica. 238. 656–667.

4.

Senn, Walter, Dominik Dold, Ákos F. Kungl, et al.. (2024). A neuronal least-action principle for real-time learning in cortical circuits. eLife. 12. 1 indexed citations

5.

Dold, Dominik, et al.. (2023). Differentiable graph-structured models for inverse design of lattice materials. Cell Reports Physical Science. 4(10). 101586–101586. 10 indexed citations

6.

Senn, Walter, Dominik Dold, Ákos F. Kungl, et al.. (2023). A neuronal least-action principle for real-time learning in cortical circuits. eLife. 12. 2 indexed citations

7.

Dold, Dominik & Katja Fahrion. (2022). Evaluating the feasibility of interpretable machine learning for globular cluster detection. Astronomy and Astrophysics. 663. A81–A81. 1 indexed citations

8.

Dold, Dominik. (2022). Relational representation learning with spike trains. 2022 International Joint Conference on Neural Networks (IJCNN). 11. 1–8. 2 indexed citations

9.

Dold, Dominik, et al.. (2022). Neuro-symbolic computing with spiking neural networks. 1–4. 4 indexed citations

10.

Dold, Dominik, et al.. (2022). Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods. 381–388. 3 indexed citations

11.

Kriener, Laura, Sebastian Billaudelle, Oliver Breitwieser, et al.. (2019). Fast and energy-efficient neuromorphic deep learning with first-spike times. arXiv (Cornell University). 76 indexed citations

12.

Dold, Dominik, Ákos F. Kungl, Oliver Breitwieser, et al.. (2019). Stochasticity from function — Why the Bayesian brain may need no noise. Neural Networks. 119. 200–213. 15 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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