Di Shi

29 total papers · 753 total citations
22 papers, 480 citations indexed

About

Di Shi is a scholar working on Biomedical Engineering, Rehabilitation and Surgery. According to data from OpenAlex, Di Shi has authored 22 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Biomedical Engineering, 14 papers in Rehabilitation and 5 papers in Surgery. Recurrent topics in Di Shi's work include Prosthetics and Rehabilitation Robotics (19 papers), Stroke Rehabilitation and Recovery (14 papers) and Muscle activation and electromyography studies (14 papers). Di Shi is often cited by papers focused on Prosthetics and Rehabilitation Robotics (19 papers), Stroke Rehabilitation and Recovery (14 papers) and Muscle activation and electromyography studies (14 papers). Di Shi collaborates with scholars based in China. Di Shi's co-authors include Wuxiang Zhang, Xilun Ding, Wei Zhang, Wei Zhang, Lei Sun, Yapeng Wang, Yunhai Geng, Hang Xiao, Yanqiu Zhang and Yixin Shao and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Biomedical Engineering and Sensors.

In The Last Decade

Di Shi

18 papers receiving 468 citations

Hit Papers

A Review on Lower Limb Re... 2019 2026 2021 2023 2019 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Di Shi 404 281 56 33 26 22 480
Minh Tran 451 1.1× 145 0.5× 34 0.6× 52 1.6× 25 1.0× 13 511
Young Jin Park 372 0.9× 158 0.6× 44 0.8× 59 1.8× 31 1.2× 35 547
Manuel Cestari 423 1.0× 158 0.6× 40 0.7× 18 0.5× 33 1.3× 19 466
Youngmok Yun 402 1.0× 260 0.9× 99 1.8× 22 0.7× 29 1.1× 23 548
Hala Rifaï 402 1.0× 192 0.7× 96 1.7× 23 0.7× 75 2.9× 26 524
Jing Qiu 323 0.8× 170 0.6× 71 1.3× 22 0.7× 27 1.0× 54 496
Minhyung Lee 360 0.9× 186 0.7× 32 0.6× 54 1.6× 30 1.2× 19 414
Nicola Lotti 365 0.9× 194 0.7× 30 0.5× 27 0.8× 36 1.4× 25 425
Michael Bernhardt 269 0.7× 193 0.7× 52 0.9× 29 0.9× 30 1.2× 17 427
Du-Xin Liu 349 0.9× 177 0.6× 27 0.5× 49 1.5× 17 0.7× 21 416

Countries citing papers authored by Di Shi

Since Specialization
Citations

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

Fields of papers citing papers by Di Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Di Shi

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

All Works

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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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