Michael Hersche

1.0k total citations
17 papers, 446 citations indexed

About

Michael Hersche is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Michael Hersche has authored 17 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Electrical and Electronic Engineering, 10 papers in Artificial Intelligence and 6 papers in Cognitive Neuroscience. Recurrent topics in Michael Hersche's work include Advanced Memory and Neural Computing (11 papers), Ferroelectric and Negative Capacitance Devices (8 papers) and Neural Networks and Reservoir Computing (7 papers). Michael Hersche is often cited by papers focused on Advanced Memory and Neural Computing (11 papers), Ferroelectric and Negative Capacitance Devices (8 papers) and Neural Networks and Reservoir Computing (7 papers). Michael Hersche collaborates with scholars based in Switzerland, Italy and Germany. Michael Hersche's co-authors include Luca Benini, Abbas Rahimi, Xiaying Wang, Lukas Cavigelli, Nobuaki Kobayashi, Abu Sebastian, Thorir Mar Ingolfsson, Geethan Karunaratne, Giovanni Cherubini and Michele Magno and has published in prestigious journals such as Nature Nanotechnology, IEEE Sensors Journal and Nature Machine Intelligence.

In The Last Decade

Michael Hersche

15 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Hersche Switzerland 10 210 193 167 85 55 17 446
Huihui Zhou China 7 286 1.4× 199 1.0× 112 0.7× 64 0.8× 42 0.8× 17 446
Shang-Lin Wu Taiwan 10 310 1.5× 86 0.4× 135 0.8× 99 1.2× 119 2.2× 16 528
Sumit Bam Shrestha Singapore 11 160 0.8× 206 1.1× 124 0.7× 56 0.7× 31 0.6× 16 325
Morteza Alamgir Germany 7 342 1.6× 99 0.5× 80 0.5× 122 1.4× 67 1.2× 10 481
Jinfu Yang China 12 274 1.3× 73 0.4× 84 0.5× 124 1.5× 59 1.1× 34 420
Feifei Qi China 8 327 1.6× 87 0.5× 72 0.4× 111 1.3× 70 1.3× 17 448
Fatemeh Fahimi Singapore 5 344 1.6× 93 0.5× 52 0.3× 92 1.1× 62 1.1× 11 420
Wenlong Hang China 10 157 0.7× 47 0.2× 130 0.8× 47 0.6× 63 1.1× 25 380
Seul-Ki Yeom South Korea 7 196 0.9× 57 0.3× 85 0.5× 85 1.0× 40 0.7× 10 347

Countries citing papers authored by Michael Hersche

Since Specialization
Citations

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

Fields of papers citing papers by Michael Hersche

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Hersche

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Hersche. A scholar is included among the top collaborators of Michael Hersche 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 Michael Hersche. Michael Hersche 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.
Karunaratne, Geethan, et al.. (2024). Zero-Shot Classification Using Hyperdimensional Computing. 1–2. 1 indexed citations
2.
Ingolfsson, Thorir Mar, et al.. (2024). 12 mJ Per Class On-Device Online Few-Shot Class-Incremental Learning. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1–6.
3.
Hersche, Michael, Geethan Karunaratne, Giovanni Cherubini, et al.. (2024). Factorizers for distributed sparse block codes. 1.
4.
Wang, Xiaying, Michael Hersche, Michele Magno, & Luca Benini. (2024). MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain–Machine Interfaces With EEG Channel Selection. IEEE Sensors Journal. 24(6). 8835–8847. 25 indexed citations
5.
Karunaratne, Geethan, et al.. (2023). In-memory factorization of holographic perceptual representations. Nature Nanotechnology. 18(5). 479–485. 20 indexed citations
6.
Hersche, Michael, et al.. (2023). A neuro-vector-symbolic architecture for solving Raven’s progressive matrices. Nature Machine Intelligence. 5(4). 363–375. 37 indexed citations
7.
Hersche, Michael, Geethan Karunaratne, Giovanni Cherubini, et al.. (2022). Constrained Few-shot Class-incremental Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9047–9057. 100 indexed citations
8.
Karunaratne, Geethan, Michael Hersche, Giovanni Cherubini, et al.. (2022). In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit Memory. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 105–108. 11 indexed citations
9.
Hersche, Michael, et al.. (2021). Near-channel classifier: symbiotic communication and classification in high-dimensional space. Brain Informatics. 8(1). 16–16. 10 indexed citations
10.
Wang, Xiaying, et al.. (2021). Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain-Machine Interfaces. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 662. 1–5. 5 indexed citations
11.
Karunaratne, Geethan, Manuel Le Gallo, Michael Hersche, et al.. (2021). Energy Efficient In-Memory Hyperdimensional Encoding for Spatio-Temporal Signal Processing. IEEE Transactions on Circuits & Systems II Express Briefs. 68(5). 1725–1729. 13 indexed citations
12.
Ingolfsson, Thorir Mar, Michael Hersche, Xiaying Wang, et al.. (2020). EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 181 indexed citations
13.
Hersche, Michael, et al.. (2020). Integrating event-based dynamic vision sensors with sparse hyperdimensional computing. Repository for Publications and Research Data (ETH Zurich). 169–174. 17 indexed citations
14.
Hersche, Michael, et al.. (2020). Evolvable Hyperdimensional Computing: Unsupervised Regeneration of Associative Memory to Recover Faulty Components. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 281–285. 6 indexed citations
15.
Hersche, Michael, Philipp Rupp, Luca Benini, & Abbas Rahimi. (2020). Compressing Subject-specific Brain-Computer Interface Models into One Model by Superposition in Hyperdimensional Space. Repository for Publications and Research Data (ETH Zurich). 246–251. 8 indexed citations
16.
Hersche, Michael, Luca Benini, & Abbas Rahimi. (2020). Binary Models for Motor-Imagery Brain-Computer Interfaces: Sparse Random Projection and Binarized SVM. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 163–167. 1 indexed citations
17.
Hersche, Michael, et al.. (2018). Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral Features. Repository for Publications and Research Data (ETH Zurich). 11 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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