Bernhard Vogginger

747 total citations
36 papers, 297 citations indexed

About

Bernhard Vogginger is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Bernhard Vogginger has authored 36 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Electrical and Electronic Engineering, 12 papers in Artificial Intelligence and 9 papers in Cognitive Neuroscience. Recurrent topics in Bernhard Vogginger's work include Advanced Memory and Neural Computing (26 papers), Ferroelectric and Negative Capacitance Devices (17 papers) and Neural Networks and Reservoir Computing (8 papers). Bernhard Vogginger is often cited by papers focused on Advanced Memory and Neural Computing (26 papers), Ferroelectric and Negative Capacitance Devices (17 papers) and Neural Networks and Reservoir Computing (8 papers). Bernhard Vogginger collaborates with scholars based in Germany, United Kingdom and Sweden. Bernhard Vogginger's co-authors include Christian Mayr, Chen Liu, Hector A. Gonzalez, Johannes Partzsch, Sebastian Höppner, Steve Furber, Anders Lansner, Terrence C. Stewart, René Schüffny and David Kappel and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Bernhard Vogginger

32 papers receiving 292 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bernhard Vogginger Germany 11 232 110 98 68 44 36 297
Gregor Lenz France 5 274 1.2× 134 1.2× 126 1.3× 73 1.1× 10 0.2× 12 361
Stefan Scholze Germany 12 345 1.5× 143 1.3× 83 0.8× 166 2.4× 8 0.2× 32 416
Cédric Meyer France 4 284 1.2× 157 1.4× 57 0.6× 66 1.0× 36 0.8× 5 358
Amirreza Yousefzadeh Netherlands 13 356 1.5× 136 1.2× 114 1.2× 118 1.7× 11 0.3× 37 396
X. Arreguit Switzerland 8 272 1.2× 93 0.8× 50 0.5× 88 1.3× 12 0.3× 17 321
Amar Shrestha United States 10 233 1.0× 120 1.1× 97 1.0× 67 1.0× 7 0.2× 16 271
Oliver Rhodes United Kingdom 9 205 0.9× 128 1.2× 59 0.6× 78 1.1× 21 0.5× 19 263
Adarsh Kumar Kosta United States 8 167 0.7× 69 0.6× 79 0.8× 21 0.3× 8 0.2× 18 222
Junseok Kim South Korea 9 265 1.1× 28 0.3× 34 0.3× 45 0.7× 30 0.7× 24 331
Diederik Paul Moeys Switzerland 8 208 0.9× 59 0.5× 38 0.4× 52 0.8× 27 0.6× 13 299

Countries citing papers authored by Bernhard Vogginger

Since Specialization
Citations

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

Fields of papers citing papers by Bernhard Vogginger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bernhard Vogginger

This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard Vogginger. A scholar is included among the top collaborators of Bernhard Vogginger 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 Bernhard Vogginger. Bernhard Vogginger 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.
Rostami, Ali, Stefan Scholze, M. Berthel, et al.. (2025). NLU: An Adaptive, Small-Footprint, Low-Power Neural Learning Unit for Edge and IoT Applications. SHILAP Revista de lepidopterología. 6. 85–99.
2.
3.
Liu, Chen, et al.. (2024). CA-CFAR is Convolution: Fast Target Detection with Machine Learning Accelerator. 1–6. 1 indexed citations
4.
Lenz, Gregor, Dylan R. Muir, Peng Zhou, et al.. (2024). Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing. Nature Communications. 15(1). 8122–8122. 24 indexed citations
5.
Gonzalez, Hector A., et al.. (2024). A Low-footprint FFT Accelerator for a RISC-V-based Multi-core DSP in FMCW Radars. 1–5. 1 indexed citations
6.
7.
Vogginger, Bernhard, et al.. (2024). Language Modeling on a SpiNNaker2 Neuromorphic Chip. 492–496. 4 indexed citations
8.
9.
Vogginger, Bernhard, et al.. (2023). Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2. Frontiers in Neuroscience. 17. 1223262–1223262. 1 indexed citations
10.
Liu, Chen, et al.. (2022). Time-Coded Spiking Fourier Transform in Neuromorphic Hardware. IEEE Transactions on Computers. 71(11). 2792–2802. 9 indexed citations
11.
Gonzalez, Hector A., Chen Liu, Bernhard Vogginger, et al.. (2022). Efficient DBSCAN Implementation in a Multi-core DSP for FMCW Radars. 1–6. 2 indexed citations
12.
Vogginger, Bernhard, et al.. (2022). E-prop on SpiNNaker 2: Exploring online learning in spiking RNNs on neuromorphic hardware. Frontiers in Neuroscience. 16. 1018006–1018006. 13 indexed citations
13.
Vogginger, Bernhard, Chen Liu, Hector A. Gonzalez, et al.. (2022). Automotive Radar Processing With Spiking Neural Networks: Concepts and Challenges. Frontiers in Neuroscience. 16. 851774–851774. 17 indexed citations
14.
Gonzalez, Hector A., Chen Liu, Bernhard Vogginger, et al.. (2021). Ultra-High Compression of Twiddle Factor ROMs in Multi-Core DSP for FMCW Radars. 3. 1–5. 4 indexed citations
15.
Liu, Chen, Johannes Partzsch, David Kappel, et al.. (2020). Event-based Neural Network for ECG Classification with Delta Encoding and Early Stopping. GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen). 1–4. 6 indexed citations
16.
Höppner, Sebastian, Bernhard Vogginger, Stefan Scholze, et al.. (2019). Dynamic Power Management for Neuromorphic Many-Core Systems. IEEE Transactions on Circuits and Systems I Regular Papers. 66(8). 2973–2986. 15 indexed citations
17.
Liu, Chen, Guillaume Bellec, Bernhard Vogginger, et al.. (2018). Memory-Efficient Deep Learning on a SpiNNaker 2 Prototype. Frontiers in Neuroscience. 12(4). 70–71. 32 indexed citations
18.
Vogginger, Bernhard, et al.. (2015). Reducing the computational footprint for real-time BCPNN learning. Frontiers in Neuroscience. 9. 2–2. 10 indexed citations
19.
Petrovici, Mihai A., Bernhard Vogginger, Paul Müller, et al.. (2014). Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms. PLoS ONE. 9(10). e108590–e108590. 34 indexed citations
20.
Partzsch, Johannes, Christian Mayr, Bernhard Vogginger, et al.. (2013). Live demonstration: Ethernet communication linking two large-scale neuromorphic systems. Research Explorer (The University of Manchester). 5. 1–1. 2 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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