João Bimbo

1.5k total citations · 1 hit paper
36 papers, 1.1k citations indexed

About

João Bimbo is a scholar working on Biomedical Engineering, Control and Systems Engineering and Cognitive Neuroscience. According to data from OpenAlex, João Bimbo has authored 36 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Biomedical Engineering, 23 papers in Control and Systems Engineering and 19 papers in Cognitive Neuroscience. Recurrent topics in João Bimbo's work include Robot Manipulation and Learning (23 papers), Soft Robotics and Applications (15 papers) and Tactile and Sensory Interactions (15 papers). João Bimbo is often cited by papers focused on Robot Manipulation and Learning (23 papers), Soft Robotics and Applications (15 papers) and Tactile and Sensory Interactions (15 papers). João Bimbo collaborates with scholars based in Italy, United Kingdom and United States. João Bimbo's co-authors include Hongbin Liu, Shan Luo, Kaspar Althoefer, Ravinder Dahiya, Domenico Prattichizzo, Lakmal Seneviratne, Claudio Pacchierotti, Nikos G. Tsagarakis, Xiaojing Song and Helge Würdemann and has published in prestigious journals such as Sensors, The International Journal of Robotics Research and IEEE Transactions on Robotics.

In The Last Decade

João Bimbo

36 papers receiving 1.1k citations

Hit Papers

Robotic tactile perception of object properties: A review 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
João Bimbo Italy 17 666 551 511 266 158 36 1.1k
Vincent Duchaine Canada 20 1.1k 1.6× 529 1.0× 617 1.2× 345 1.3× 135 0.9× 49 1.5k
Perla Maiolino United Kingdom 18 996 1.5× 583 1.1× 405 0.8× 337 1.3× 118 0.7× 79 1.4k
Véronique Perdereau France 14 716 1.1× 442 0.8× 641 1.3× 189 0.7× 99 0.6× 41 1.1k
Philipp Mittendorfer Germany 12 854 1.3× 580 1.1× 371 0.7× 162 0.6× 152 1.0× 21 1.1k
Alexander Schmitz Japan 19 1.1k 1.7× 816 1.5× 595 1.2× 235 0.9× 159 1.0× 83 1.6k
Makoto Shimojo Japan 21 1.0k 1.5× 393 0.7× 703 1.4× 353 1.3× 89 0.6× 128 1.4k
Keehoon Kim South Korea 19 861 1.3× 510 0.9× 265 0.5× 240 0.9× 138 0.9× 97 1.3k
Shan Luo United Kingdom 21 748 1.1× 752 1.4× 427 0.8× 246 0.9× 216 1.4× 71 1.5k
Ashish Dutta India 19 681 1.0× 334 0.6× 373 0.7× 139 0.5× 109 0.7× 131 1.4k
Chaoyang Song China 16 756 1.1× 294 0.5× 328 0.6× 322 1.2× 88 0.6× 66 1.1k

Countries citing papers authored by João Bimbo

Since Specialization
Citations

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

Fields of papers citing papers by João Bimbo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of João Bimbo

This figure shows the co-authorship network connecting the top 25 collaborators of João Bimbo. A scholar is included among the top collaborators of João Bimbo 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 João Bimbo. João Bimbo 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.
Bimbo, João, Andrew S. Morgan, & Aaron M. Dollar. (2022). Force-Based Simultaneous Mapping and Object Reconstruction for Robotic Manipulation. IEEE Robotics and Automation Letters. 7(2). 4749–4756. 6 indexed citations
2.
Bimbo, João, et al.. (2020). Quasi-static analysis of planar sliding using friction patches. Use Siena air (University of Siena). 11 indexed citations
3.
Bimbo, João, et al.. (2020). Trajectory Control for 3 Degree-of-Freedom Wrist Prosthesis in Virtual Reality: A Pilot Study. 181. 765–772. 2 indexed citations
4.
Bimbo, João, et al.. (2019). Exploiting Robot Hand Compliance and Environmental Constraints for Edge Grasps. Frontiers in Robotics and AI. 6. 135–135. 15 indexed citations
5.
Naceri, Abdeldjallil, João Bimbo, Domenico Prattichizzo, et al.. (2019). Towards a Virtual Reality Interface for Remote Robotic Teleoperation. 284–289. 28 indexed citations
6.
Faragasso, Angela, João Bimbo, Agostino Stilli, et al.. (2018). Real-Time Vision-Based Stiffness Mapping †. Sensors. 18(5). 1347–1347. 8 indexed citations
7.
Pozzi, María, Gionata Salvietti, João Bimbo, Monica Malvezzi, & Domenico Prattichizzo. (2018). The Closure Signature: A Functional Approach to Model Underactuated Compliant Robotic Hands. IEEE Robotics and Automation Letters. 3(3). 2206–2213. 15 indexed citations
8.
Luo, Shan, João Bimbo, Ravinder Dahiya, & Hongbin Liu. (2017). Robotic Tactile Perception of Object Properties: A Review. arXiv (Cornell University). 5 indexed citations
9.
Bimbo, João, Claudio Pacchierotti, Marco Aggravi, Nikos G. Tsagarakis, & Domenico Prattichizzo. (2017). Teleoperation in cluttered environments using wearable haptic feedback. Use Siena air (University of Siena). 3401–3408. 62 indexed citations
10.
Luo, Shan, João Bimbo, Ravinder Dahiya, & Hongbin Liu. (2017). Robotic tactile perception of object properties: A review. Mechatronics. 48. 54–67. 301 indexed citations breakdown →
11.
Noh, Yohan, João Bimbo, Sina Sareh, et al.. (2016). Multi-Axis Force/Torque Sensor Based on Simply-Supported Beam and Optoelectronics. Sensors. 16(11). 1936–1936. 51 indexed citations
12.
Noh, Yohan, João Bimbo, Agostino Stilli, et al.. (2016). A new miniaturised multi-axis force/torque sensors based on optoelectronic technology and simply-supported beam. 23. 202–207. 6 indexed citations
13.
Faragasso, Angela, Agostino Stilli, João Bimbo, Helge Würdemann, & Kaspar Althoefer. (2015). Multi-axis stiffness sensing device for medical palpation. Research Portal (King's College London). 2711–2716. 17 indexed citations
14.
Bimbo, João, Petar Kormushev, Kaspar Althoefer, & Hongbin Liu. (2015). Global estimation of an object’s pose using tactile sensing. Advanced Robotics. 29(5). 363–374. 31 indexed citations
15.
Liu, Hongbin, Véronique Perdereau, João Bimbo, et al.. (2015). Finger contact sensing and the application in dexterous hand manipulation. Autonomous Robots. 39(1). 25–41. 51 indexed citations
16.
Faragasso, Angela, Agostino Stilli, João Bimbo, et al.. (2014). Endoscopic add-on stiffness probe for real-time soft surface characterisation in MIS. PubMed. 2014. 6517–6520. 16 indexed citations
17.
Song, Xiaojing, Hongbin Liu, João Bimbo, Kaspar Althoefer, & Lakmal Seneviratne. (2012). Object surface classificaiton based on friction properties for intelligent robotic hands. World Automation Congress. 1–5. 6 indexed citations
18.
Bimbo, João, et al.. (2012). Object pose estimation and tracking by fusing visual and tactile information. 65–70. 19 indexed citations
19.
Liu, Hongbin, et al.. (2012). Tactile image based contact shape recognition using neural network. 138–143. 52 indexed citations
20.
Jiang, Allen, João Bimbo, Hongbin Liu, et al.. (2012). Adaptive grip control on an uncertain object. Research Portal (King's College London). 1161–1166. 6 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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