Yuki Usami

602 total citations
38 papers, 427 citations indexed

About

Yuki Usami is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Yuki Usami has authored 38 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Electrical and Electronic Engineering, 20 papers in Artificial Intelligence and 7 papers in Cognitive Neuroscience. Recurrent topics in Yuki Usami's work include Advanced Memory and Neural Computing (24 papers), Neural Networks and Reservoir Computing (20 papers) and Neural dynamics and brain function (7 papers). Yuki Usami is often cited by papers focused on Advanced Memory and Neural Computing (24 papers), Neural Networks and Reservoir Computing (20 papers) and Neural dynamics and brain function (7 papers). Yuki Usami collaborates with scholars based in Japan, Thailand and United States. Yuki Usami's co-authors include Hirofumi Tanaka, Saman Azhari, Hakaru Tamukoh, Takuya Matsumoto, H. Ohoyama, Noriyuki Kumazawa, Yoshihiro Shigemasa, Yoichi Otsuka, Yuichiro Tanaka and Wilfred G. van der Wiel and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Applied Physics Letters.

In The Last Decade

Yuki Usami

33 papers receiving 423 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuki Usami Japan 10 276 207 91 55 44 38 427
Wenbin Zhang China 7 237 0.9× 66 0.3× 29 0.3× 146 2.7× 132 3.0× 14 456
Jaesung Park South Korea 8 389 1.4× 52 0.3× 58 0.6× 40 0.7× 9 0.2× 11 528
Zheng Chai United Kingdom 15 417 1.5× 62 0.3× 23 0.3× 64 1.2× 27 0.6× 39 547
Zelin Cao China 14 605 2.2× 75 0.4× 84 0.9× 59 1.1× 11 0.3× 55 828
Ella Gale United Kingdom 11 320 1.2× 37 0.2× 90 1.0× 65 1.2× 45 1.0× 33 449
Ran Liu China 15 79 0.3× 30 0.1× 91 1.0× 215 3.9× 21 0.5× 43 602
Seongyeon Kim South Korea 10 227 0.8× 22 0.1× 40 0.4× 182 3.3× 10 0.2× 30 440
Yafeng Hao China 8 124 0.4× 52 0.3× 23 0.3× 179 3.3× 14 0.3× 19 399
Alexander Derry United States 7 77 0.3× 32 0.2× 35 0.4× 133 2.4× 18 0.4× 9 412
Ling Qin China 7 273 1.0× 29 0.1× 17 0.2× 52 0.9× 27 0.6× 12 353

Countries citing papers authored by Yuki Usami

Since Specialization
Citations

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

Fields of papers citing papers by Yuki Usami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuki Usami

This figure shows the co-authorship network connecting the top 25 collaborators of Yuki Usami. A scholar is included among the top collaborators of Yuki Usami 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 Yuki Usami. Yuki Usami 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
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Usami, Yuki, et al.. (2025). Performance of in-materio physical reservoir computing devices based on highly oriented semiconducting polymer thin films. Japanese Journal of Applied Physics. 64(4). 04SP12–04SP12. 1 indexed citations
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Obara, Keisuke, et al.. (2024). Evaluation of inhibitory actions of antidepressants on muscarinic receptors assessed by a binding assay in the mouse cerebral neocortex. Journal of Pharmacological Sciences. 156(4). 214–217.
6.
Tanaka, Yuichiro, et al.. (2024). Object recognition and grasping point detection using carbon nanotube - polydimethylsiloxane nanocomposite sensor. Nonlinear Theory and Its Applications IEICE. 15(4). 883–898. 1 indexed citations
7.
Stieg, Adam Z., James K. Gimzewski, Yuichiro Tanaka, et al.. (2024). Thermally Stable Ag2Se Nanowire Network as an Effective In‐Materio Physical Reservoir Computing Device. Advanced Electronic Materials. 10(12). 3 indexed citations
8.
Abdi, Gisya, et al.. (2024). Mel-frequency cepstral coefficients feature extracted voice recognition task using atomic switch Ag/Ag<sub>2</sub>S device-based time-delayed reservoir computing. Nonlinear Theory and Its Applications IEICE. 15(4). 871–882. 2 indexed citations
9.
Azhari, Saman, et al.. (2024). Haptic In‐Sensor Computing Device Based on CNT/PDMS Nanocomposite Physical Reservoir. SHILAP Revista de lepidopterología. 7(3). 3 indexed citations
10.
Azhari, Saman, et al.. (2024). Effect of nonlinearity induced by atomic switch in Ag/Ag2S nanoparticles on performance of in-materio reservoir computing. Applied Physics Letters. 124(9). 3 indexed citations
11.
Azhari, Saman, et al.. (2023). High Performance of an In-Material Reservoir Computing Device Achieved by Complex Dynamics in a Nanoparticle Random Network Memristor. ACS Applied Electronic Materials. 6(2). 688–695. 13 indexed citations
12.
Usami, Yuki, et al.. (2023). Performance improvement of in-materio reservoir computing by noise injection. Japanese Journal of Applied Physics. 62(SG). SG1042–SG1042. 7 indexed citations
13.
Azhari, Saman, Gábor Méhes, Yuki Usami, et al.. (2023). Integration of Wireless Power Transfer Technology With Hierarchical Multiwalled Carbon Nanotubes-Polydimethylsiloxane Piezo-Responsive Pressure Sensor for Remote Force Measurement. IEEE Sensors Journal. 23(7). 7902–7909. 5 indexed citations
14.
Inose, Tomoko, Shuichi Toyouchi, Peter Walke, et al.. (2023). Visualizing Ribbon‐to‐Ribbon Heterogeneity of Chemically Unzipped Wide Graphene Nanoribbons by Silver Nanowire‐Based Tip‐Enhanced Raman Scattering Microscopy. Small. 20(3). e2301841–e2301841. 2 indexed citations
15.
Usami, Yuki, et al.. (2022). In-materio reservoir working at low frequencies in a Ag2S-island network. Nanoscale. 14(20). 7634–7640. 22 indexed citations
16.
Tanaka, Hirofumi, et al.. (2022). In-materio computing in random networks of carbon nanotubes complexed with chemically dynamic molecules: a review. Neuromorphic Computing and Engineering. 2(2). 22002–22002. 17 indexed citations
17.
Azhari, Saman, Yuki Usami, Takuji Ogawa, et al.. (2022). Emergence of In‐Materio Intelligence from an Incidental Structure of a Single‐Walled Carbon Nanotube–Porphyrin Polyoxometalate Random Network. SHILAP Revista de lepidopterología. 4(4). 40 indexed citations
18.
Usami, Yuki, et al.. (2021). Performance of Ag–Ag 2 S core–shell nanoparticle-based random network reservoir computing device. Japanese Journal of Applied Physics. 60(SC). SCCF02–SCCF02. 24 indexed citations
19.
Usami, Yuki, Tao Chen, Yuichiro Tanaka, et al.. (2021). In‐Materio Reservoir Computing in a Sulfonated Polyaniline Network. Advanced Materials. 33(48). e2102688–e2102688. 99 indexed citations
20.
Usami, Yuki, et al.. (2020). Frequency dependence dielectrophoresis technique for bridging graphene nanoribbons. Applied Physics Express. 13(10). 101004–101004. 4 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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