Juan Aparicio Ojea

1.2k total citations
10 papers, 539 citations indexed

About

Juan Aparicio Ojea is a scholar working on Control and Systems Engineering, Biomedical Engineering and Aerospace Engineering. According to data from OpenAlex, Juan Aparicio Ojea has authored 10 papers receiving a total of 539 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Control and Systems Engineering, 4 papers in Biomedical Engineering and 2 papers in Aerospace Engineering. Recurrent topics in Juan Aparicio Ojea's work include Robot Manipulation and Learning (7 papers), Soft Robotics and Applications (3 papers) and Manufacturing Process and Optimization (2 papers). Juan Aparicio Ojea is often cited by papers focused on Robot Manipulation and Learning (7 papers), Soft Robotics and Applications (3 papers) and Manufacturing Process and Optimization (2 papers). Juan Aparicio Ojea collaborates with scholars based in United States, Germany and Israel. Juan Aparicio Ojea's co-authors include Chris Develder, Kevin Mets, Eugen Solowjow, Jianlan Luo, Chengtao Wen, Alice M. Agogino, Aviv Tamar, Pieter Abbeel, Ken Goldberg and Jeannette Bohg and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, Transportation Research Record Journal of the Transportation Research Board and IEEE Robotics and Automation Letters.

In The Last Decade

Juan Aparicio Ojea

10 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Juan Aparicio Ojea United States 8 423 153 116 109 69 10 539
Cihan Karakuzu Türkiye 12 155 0.4× 69 0.5× 139 1.2× 183 1.7× 84 1.2× 34 517
Edgar Alfredo Portilla-Flores Mexico 14 211 0.5× 57 0.4× 38 0.3× 101 0.9× 99 1.4× 63 458
C.W. de Silva Canada 13 479 1.1× 64 0.4× 36 0.3× 96 0.9× 209 3.0× 56 684
Sarosh Patel United States 10 244 0.6× 134 0.9× 39 0.3× 60 0.6× 131 1.9× 44 473
Jairo Viola United States 12 357 0.8× 51 0.3× 81 0.7× 57 0.5× 89 1.3× 64 556
José Araújo Sweden 13 311 0.7× 66 0.4× 172 1.5× 53 0.5× 76 1.1× 28 684
Bakir Lačević Bosnia and Herzegovina 14 433 1.0× 148 1.0× 36 0.3× 117 1.1× 109 1.6× 50 696
José Simó Spain 11 108 0.3× 52 0.3× 126 1.1× 72 0.7× 78 1.1× 76 576

Countries citing papers authored by Juan Aparicio Ojea

Since Specialization
Citations

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

Fields of papers citing papers by Juan Aparicio Ojea

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Juan Aparicio Ojea. 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 Juan Aparicio Ojea. The network helps show where Juan Aparicio Ojea may publish in the future.

Co-authorship network of co-authors of Juan Aparicio Ojea

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

All Works

10 of 10 papers shown
1.
Shao, Lin, Mikael Jorda, Jianlan Luo, et al.. (2020). UniGrasp: Learning a Unified Model to Grasp With Multifingered Robotic Hands. IEEE Robotics and Automation Letters. 5(2). 2286–2293. 66 indexed citations
2.
Song, Jingyi, Ajay Kumar Tanwani, Jeffrey Ichnowski, et al.. (2020). Robust Task-Based Grasping as a Service. 5 indexed citations
3.
Luo, Jianlan, Eugen Solowjow, Juan Aparicio Ojea, et al.. (2019). Domain Randomization for Active Pose Estimation. 7228–7234. 21 indexed citations
4.
Luo, Jianlan, Eugen Solowjow, Chengtao Wen, et al.. (2019). Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly. 3080–3087. 123 indexed citations
5.
6.
Mahler, Jeffrey, et al.. (2018). Dex-Net as a Service (DNaaS): A Cloud-Based Robust Robot Grasp Planning System. 1420–1427. 19 indexed citations
7.
Luo, Jianlan, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, & Alice M. Agogino. (2018). Deep Reinforcement Learning for Robotic Assembly of Mixed Deformable and Rigid Objects. 2062–2069. 62 indexed citations
8.
Gealy, David V., Jacky Liang, Jeffrey Mahler, et al.. (2017). Design of parallel-jaw gripper tip surfaces for robust grasping. 2831–2838. 33 indexed citations
9.
Songchitruksa, Praprut, et al.. (2017). Interlinking Vissim and ns-3 for Connected Vehicle Simulation: Case Study of Intelligent Dilemma Zone Avoidance. Transportation Research Record Journal of the Transportation Research Board. 2619(1). 36–43. 4 indexed citations
10.
Mets, Kevin, Juan Aparicio Ojea, & Chris Develder. (2014). Combining Power and Communication Network Simulation for Cost-Effective Smart Grid Analysis. IEEE Communications Surveys & Tutorials. 16(3). 1771–1796. 179 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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