Shingo Murata

3.5k total citations
73 papers, 2.3k citations indexed

About

Shingo Murata is a scholar working on Mechanical Engineering, Control and Systems Engineering and Cognitive Neuroscience. According to data from OpenAlex, Shingo Murata has authored 73 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Mechanical Engineering, 23 papers in Control and Systems Engineering and 18 papers in Cognitive Neuroscience. Recurrent topics in Shingo Murata's work include Modular Robots and Swarm Intelligence (28 papers), Robot Manipulation and Learning (19 papers) and Advanced Materials and Mechanics (15 papers). Shingo Murata is often cited by papers focused on Modular Robots and Swarm Intelligence (28 papers), Robot Manipulation and Learning (19 papers) and Advanced Materials and Mechanics (15 papers). Shingo Murata collaborates with scholars based in Japan, South Korea and United Kingdom. Shingo Murata's co-authors include S. Kokaji, H. Kurokawa, Kohji Tomita, Eiichi Yoshida, Akiya Kamimura, Hiroaki Kurokawa, Tetsuya Ogata, Hiroaki Arie, Shigeki Sugano and Jun Tani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Industrial Electronics.

In The Last Decade

Shingo Murata

68 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shingo Murata Japan	24	1.8k	814	753	487	470	73	2.3k
Kohji Tomita Japan	21	1.9k 1.1×	909 1.1×	807 1.1×	539 1.1×	428 0.9×	100	2.2k
Behnam Salemi United States	12	1.4k 0.8×	621 0.8×	600 0.8×	410 0.8×	342 0.7×	25	1.6k
Kasper Støy Denmark	20	1.1k 0.6×	362 0.4×	419 0.6×	471 1.0×	323 0.7×	85	1.6k
Ali Emre Turgut Türkiye	21	490 0.3×	201 0.2×	138 0.2×	590 1.2×	103 0.2×	45	1.1k
Josie Hughes Switzerland	21	614 0.3×	230 0.3×	1.2k 1.6×	42 0.1×	578 1.2×	117	1.8k
Yangsheng Xu Hong Kong	20	362 0.2×	120 0.1×	422 0.6×	170 0.3×	1.1k 2.4×	79	2.1k
Stefano Scheggi Italy	20	453 0.3×	315 0.4×	489 0.6×	40 0.1×	196 0.4×	35	1.1k
H.E. Stephanou United States	20	434 0.2×	79 0.1×	619 0.8×	117 0.2×	514 1.1×	104	1.6k
Tony J. Dodd United Kingdom	20	362 0.2×	61 0.1×	464 0.6×	147 0.3×	461 1.0×	78	1.4k
Elio Tuci Belgium	17	397 0.2×	76 0.1×	95 0.1×	333 0.7×	191 0.4×	71	1.1k

Countries citing papers authored by Shingo Murata

Since Specialization

Citations

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

Fields of papers citing papers by Shingo Murata

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shingo Murata

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

All Works

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20 of 20 papers shown

Taniguchi, Tadahiro, Shingo Murata, Masahiro Suzuki, et al.. (2023). World models and predictive coding for cognitive and developmental robotics: frontiers and challenges. Advanced Robotics. 37(13). 780–806. 34 indexed citations

Nomura, Yuta & Shingo Murata. (2023). Real-World Robot Control and Data Augmentation by World-Model Learning from Play. 100. 133–138. 1 indexed citations

Fujii, Kentaro & Shingo Murata. (2023). Hierarchical Latent Dynamics Model with Multiple Timescales for Learning Long-Horizon Tasks. 479–485.

Nomura, Yuta, et al.. (2023). Goal-Conditioned Flexible Object Manipulation by Self-Supervised Learning from Play. 100. PMLR. 150–155. 1 indexed citations

Takahashi, Yuta, Shingo Murata, Masao Ueki, Hiroaki Tomita, & Yuichi Yamashita. (2023). Interaction between Functional Connectivity and Neural Excitability in Autism: A Novel Framework for Computational Modeling and Application to Biological Data. SHILAP Revista de lepidopterología. 7(1). 14–14. 3 indexed citations

Kobayashi, Taisuke, Shingo Murata, & Tetsunari Inamura. (2022). Latent Representation in Human–Robot Interaction With Explicit Consideration of Periodic Dynamics. IEEE Transactions on Human-Machine Systems. 52(5). 928–940. 4 indexed citations

Takahashi, Yuta, et al.. (2021). Neural network modeling of altered facial expression recognition in autism spectrum disorders based on predictive processing framework. Scientific Reports. 11(1). 14684–14684. 11 indexed citations

Ogata, Tetsuya, et al.. (2021). Tool-Use Model to Reproduce the Goal Situations Considering Relationship Among Tools, Objects, Actions and Effects Using Multimodal Deep Neural Networks. Frontiers in Robotics and AI. 8. 748716–748716. 3 indexed citations

Murata, Shingo, et al.. (2021). Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder. Neural Networks. 138. 150–163. 8 indexed citations

10.

Murata, Shingo, et al.. (2020). Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder. Frontiers in Psychiatry. 11. 762–762. 15 indexed citations

11.

Murata, Shingo, et al.. (2020). Development of Morin-Loaded Nanoemulsions Containing Various Polymers; Role of Polymers in Formulation Properties and Bioavailability. AAPS PharmSciTech. 21(5). 150–150. 6 indexed citations

12.

Kim, Kitae, et al.. (2018). Tool-Use Model Considering Tool Selection by a Robot Using Deep Learning. 313. 270–276. 8 indexed citations

13.

Yamada, Tatsuro, Shingo Murata, Hiroaki Arie, & Tetsuya Ogata. (2016). Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human–Robot Interaction. Frontiers in Neurorobotics. 10. 5–5. 25 indexed citations

14.

Murata, Shingo, et al.. (2015). Acquisition of viewpoint representation in imitative learning from own sensory-motor experiences. 326–331. 6 indexed citations

15.

Murata, Shingo, Yuichi Yamashita, Hiroaki Arie, et al.. (2014). Generation of sensory reflex behavior versus intentional proactive behavior in robot learning of cooperative interactions with others. 242–248. 5 indexed citations

16.

Murata, Shingo & Takeshi Hirose. (2005). Onboard Locating System Of Autonomous Vehicle. 228–234. 2 indexed citations

17.

Kamimura, Akiya, Shingo Murata, Eiichi Yoshida, et al.. (2002). Self-reconfigurable modular robot - experiments on reconfiguration and locomotion. 1. 606–612. 59 indexed citations

18.

Kurokawa, H., Shingo Murata, Eiichi Yoshida, Kohji Tomita, & S. Kokaji. (2002). A 3-D self-reconfigurable structure and experiments. 2. 860–865. 19 indexed citations

19.

Kobayashi, Hiroki, et al.. (2001). New MET system based on essential training concept. WIT transactions on the built environment. 53.

20.

Tsugawa, Sadayuki, et al.. (1988). Vehicle following system using vehicle-to-vehicle communication - its concept, control algorithm, and communication system. 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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