Yao Jiang

2.3k total citations · 1 hit paper
93 papers, 1.6k citations indexed

About

Yao Jiang is a scholar working on Control and Systems Engineering, Biomedical Engineering and Mechanical Engineering. According to data from OpenAlex, Yao Jiang has authored 93 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Control and Systems Engineering, 38 papers in Biomedical Engineering and 19 papers in Mechanical Engineering. Recurrent topics in Yao Jiang's work include Iterative Learning Control Systems (16 papers), Robotic Mechanisms and Dynamics (15 papers) and Tactile and Sensory Interactions (14 papers). Yao Jiang is often cited by papers focused on Iterative Learning Control Systems (16 papers), Robotic Mechanisms and Dynamics (15 papers) and Tactile and Sensory Interactions (14 papers). Yao Jiang collaborates with scholars based in China, United States and Chile. Yao Jiang's co-authors include Tiemin Li, Amy L. Lerner, Ellen Kuhl, Francisco Sahli Costabal, Liping Wang, Jordan Lee, Jason Snibbe, Fengchun Li, Julius M. Guccione and Larry A. Taber and has published in prestigious journals such as IEEE Access, Computer Methods in Applied Mechanics and Engineering and Journal of Biomechanics.

In The Last Decade

Yao Jiang

89 papers receiving 1.6k citations

Hit Papers

Precision medicine in human heart modeling 2021 2026 2022 2024 2021 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yao Jiang China 24 597 466 434 288 275 93 1.6k
Ken Masamune Japan 29 1.3k 2.2× 834 1.8× 175 0.4× 154 0.5× 124 0.5× 157 2.4k
Mehran Armand United States 31 1.6k 2.7× 1.2k 2.5× 537 1.2× 312 1.1× 82 0.3× 156 2.8k
Pier Paolo Valentini Italy 27 342 0.6× 133 0.3× 1.0k 2.3× 838 2.9× 30 0.1× 140 2.5k
Mitsunori Tada Japan 18 433 0.7× 279 0.6× 126 0.3× 55 0.2× 44 0.2× 128 1.2k
Chaoyang Shi China 25 1.3k 2.1× 335 0.7× 499 1.1× 433 1.5× 63 0.2× 121 2.3k
Chang‐Sei Kim South Korea 31 2.8k 4.6× 1.0k 2.2× 284 0.7× 609 2.1× 1.3k 4.8× 132 3.7k
Adrián Buganza Tepole United States 26 879 1.5× 333 0.7× 37 0.1× 184 0.6× 96 0.3× 95 2.2k
David Frakes United States 28 554 0.9× 611 1.3× 148 0.3× 113 0.4× 407 1.5× 98 2.1k
Rouzbeh Amini United States 22 340 0.6× 234 0.5× 175 0.4× 139 0.5× 402 1.5× 95 1.4k
Bernard Querleux France 22 347 0.6× 244 0.5× 124 0.3× 105 0.4× 27 0.1× 32 1.8k

Countries citing papers authored by Yao Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Yao Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yao Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Yao Jiang. A scholar is included among the top collaborators of Yao Jiang 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 Yao Jiang. Yao Jiang 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.
Cao, Jing, et al.. (2025). High-resolution and reliable 3D deformation measurement method for vision-based tactile sensor. Measurement. 256. 118298–118298.
2.
Li, Tiemin, et al.. (2024). EasyCalib: Simple and Low-Cost In-Situ Calibration for Force Reconstruction With Vision-Based Tactile Sensors. IEEE Robotics and Automation Letters. 9(9). 7803–7810. 1 indexed citations
3.
Li, Tiemin, et al.. (2024). Incipient Slip-Based Rotation Measurement via Visuotactile Sensing During In-Hand Object Pivoting. 17132–17138. 3 indexed citations
4.
Li, Tiemin, et al.. (2023). Measurement of mobile manipulator chassis pose change caused by suspension deformation and end-effector accuracy improvement based on multi-sensor fusion. Robotics and Autonomous Systems. 170. 104553–104553. 4 indexed citations
5.
Li, Tiemin, et al.. (2023). A Robust Incipient Slip Detection Method With Vision-Based Tactile Sensor Based on Local Deformation Degree. IEEE Sensors Journal. 23(15). 17200–17213. 6 indexed citations
6.
Li, Tiemin, et al.. (2023). Real-time and robust feature detection of continuous marker pattern for dense 3-D deformation measurement. Measurement. 221. 113479–113479. 5 indexed citations
7.
Peirlinck, Mathias, Yao Jiang, Francisco Sahli Costabal, & Ellen Kuhl. (2022). How drugs modulate the performance of the human heart. Computational Mechanics. 69(6). 1397–1411. 15 indexed citations
8.
Wisneski, Andrew D., Yunjie Wang, Salvatore Pasta, et al.. (2022). Left Ventricle Biomechanics of Low-Flow, Low-Gradient Aortic Stenosis: A Patient-Specific Computational Model. Frontiers in Physiology. 13. 848011–848011. 8 indexed citations
9.
Peirlinck, Mathias, Francisco Sahli Costabal, Yao Jiang, et al.. (2021). Precision medicine in human heart modeling. Biomechanics and Modeling in Mechanobiology. 20(3). 803–831. 134 indexed citations breakdown →
10.
Shu, Liming, Yao Jiang, Ko Yamamoto, Takashi Satō, & Naohiko Sugita. (2021). In vivo kinematical validated knee model for preclinical testing of total knee replacement. Computers in Biology and Medicine. 132. 104311–104311. 7 indexed citations
11.
Wisneski, Andrew D., Yunjie Wang, T. Deuse, et al.. (2020). Impact of Aortic Stenosis on Myofiber Stress: Translational Application of Left Ventricle-Aortic Coupling Simulation. Frontiers in Physiology. 11. 574211–574211. 14 indexed citations
12.
Costabal, Francisco Sahli, et al.. (2019). Machine learning in drug development: Characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification. Computer Methods in Applied Mechanics and Engineering. 348. 313–333. 63 indexed citations
13.
Dabiri, Yaghoub, Yao Jiang, Kevin L. Sack, Ghassan S. Kassab, & Julius M. Guccione. (2019). Tricuspid valve regurgitation decreases after mitraclip implantation: Fluid structure interaction simulation. Mechanics Research Communications. 97. 96–100. 18 indexed citations
14.
Costabal, Francisco Sahli, Yao Jiang, & Ellen Kuhl. (2018). Predicting drug‐induced arrhythmias by multiscale modeling. International Journal for Numerical Methods in Biomedical Engineering. 34(5). e2964–e2964. 34 indexed citations
15.
Costabal, Francisco Sahli, Yao Jiang, Anna Sher, & Ellen Kuhl. (2018). Predicting critical drug concentrations and torsadogenic risk using a multiscale exposure-response simulator. Progress in Biophysics and Molecular Biology. 144. 61–76. 6 indexed citations
16.
Jiang, Yao, et al.. (2017). Analytical Compliance Modeling of Serial Flexure-Based Compliant Mechanism Under Arbitrary Applied Load. Chinese Journal of Mechanical Engineering. 30(4). 951–962. 19 indexed citations
17.
Wang, Liping, Yao Jiang, & Tiemin Li. (2014). Running accuracy analysis of a 3-RRR parallel kinematic machine considering the deformations of the links. Chinese Journal of Mechanical Engineering. 27(5). 890–899. 5 indexed citations
18.
Shi, Yunfei, et al.. (2014). Bending and twisting the embryonic heart: a computational model for c-looping based on realistic geometry. Frontiers in Physiology. 5. 297–297. 30 indexed citations
19.
Jiang, Yao, et al.. (2008). Magnetic resonance image analysis of meniscal translation and tibio‐menisco‐femoral contact in deep knee flexion. Journal of Orthopaedic Research®. 26(5). 673–684. 93 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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