Yasemin Bekiroglu

1.3k total citations
43 papers, 882 citations indexed

About

Yasemin Bekiroglu is a scholar working on Control and Systems Engineering, Biomedical Engineering and Cognitive Neuroscience. According to data from OpenAlex, Yasemin Bekiroglu has authored 43 papers receiving a total of 882 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Control and Systems Engineering, 18 papers in Biomedical Engineering and 13 papers in Cognitive Neuroscience. Recurrent topics in Yasemin Bekiroglu's work include Robot Manipulation and Learning (38 papers), Muscle activation and electromyography studies (13 papers) and Reinforcement Learning in Robotics (9 papers). Yasemin Bekiroglu is often cited by papers focused on Robot Manipulation and Learning (38 papers), Muscle activation and electromyography studies (13 papers) and Reinforcement Learning in Robotics (9 papers). Yasemin Bekiroglu collaborates with scholars based in Sweden, United Kingdom and Switzerland. Yasemin Bekiroglu's co-authors include Danica Kragić, Ville Kyrki, Miao Li, Aude Billard, Jimmy Alison Jørgensen, Mårten Björkman, Rustam Stolkin, Naresh Marturi, Johannes A. Stork and Renaud Detry and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Robotics and Robotics and Autonomous Systems.

In The Last Decade

Yasemin Bekiroglu

39 papers receiving 861 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yasemin Bekiroglu Sweden 16 671 459 286 170 149 43 882
Antonio Morales Spain 19 814 1.2× 514 1.1× 138 0.5× 208 1.2× 137 0.9× 58 1.0k
Clemens Eppner Germany 16 715 1.1× 397 0.9× 103 0.4× 330 1.9× 194 1.3× 25 974
Anis Sahbani France 13 649 1.0× 407 0.9× 85 0.3× 318 1.9× 110 0.7× 48 897
Véronique Perdereau France 14 641 1.0× 716 1.6× 442 1.5× 144 0.8× 189 1.3× 41 1.1k
Ji‐Hun Bae South Korea 17 938 1.4× 653 1.4× 103 0.4× 164 1.0× 345 2.3× 93 1.2k
Sahar El-Khoury France 12 528 0.8× 372 0.8× 102 0.4× 125 0.7× 79 0.5× 17 637
Aaron Walsman United States 5 799 1.2× 450 1.0× 137 0.5× 439 2.6× 144 1.0× 8 1.1k
Leonel Rozo Italy 19 1.0k 1.5× 467 1.0× 127 0.4× 234 1.4× 282 1.9× 35 1.3k
Tokuo Tsuji Japan 18 620 0.9× 458 1.0× 70 0.2× 225 1.3× 195 1.3× 102 864

Countries citing papers authored by Yasemin Bekiroglu

Since Specialization
Citations

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

Fields of papers citing papers by Yasemin Bekiroglu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yasemin Bekiroglu

This figure shows the co-authorship network connecting the top 25 collaborators of Yasemin Bekiroglu. A scholar is included among the top collaborators of Yasemin Bekiroglu 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 Yasemin Bekiroglu. Yasemin Bekiroglu 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.
Deisenroth, Marc Peter, et al.. (2023). Grasp Transfer Based on Self-Aligning Implicit Representations of Local Surfaces. IEEE Robotics and Automation Letters. 8(10). 6315–6322. 5 indexed citations
2.
Chen, Yi‐Ting, et al.. (2023). GraspAda: Deep Grasp Adaptation through Domain Transfer. Chalmers Research (Chalmers University of Technology). 10268–10274. 5 indexed citations
3.
Deisenroth, Marc Peter, et al.. (2023). Neural Field Movement Primitives for Joint Modelling of Scenes and Motions. Chalmers Research (Chalmers University of Technology). 3648–3655. 2 indexed citations
4.
Chen, Yi-Ting, et al.. (2023). Sliding Touch-Based Exploration for Modeling Unknown Object Shape with Multi-Fingered Hands. Chalmers Research (Chalmers University of Technology). 8943–8950. 7 indexed citations
5.
Bekiroglu, Yasemin, et al.. (2023). Benchmarking local motion planners for navigation of mobile manipulators. Chalmers Research (Chalmers University of Technology). 1–6. 5 indexed citations
6.
Deisenroth, Marc Peter, et al.. (2022). Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation. 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE). 1009–1016. 5 indexed citations
7.
Lázaro-Gredilla, Miguel, Yasemin Bekiroglu, Abhishek Agarwal, et al.. (2022). DURableVS: Data-efficient Unsupervised Recalibrating Visual Servoing via online learning in a structured generative model. 2022 International Conference on Robotics and Automation (ICRA). 3. 6674–6680. 1 indexed citations
8.
Bekiroglu, Yasemin, Naresh Marturi, Máximo A. Roa, et al.. (2019). Benchmarking Protocol for Grasp Planning Algorithms. IEEE Robotics and Automation Letters. 5(2). 315–322. 24 indexed citations
9.
Marturi, Naresh, Marek Kopicki, Alireza Rastegarpanah, et al.. (2018). Dynamic grasp and trajectory planning for moving objects. Autonomous Robots. 43(5). 1241–1256. 64 indexed citations
10.
Pokorny, Florian T., et al.. (2017). A database for reproducible manipulation research: CapriDB – Capture, Print, Innovate. Data in Brief. 11. 491–498.
11.
Haage, Mathias, Ioannis Mariolis, Jacek Malec, et al.. (2017). Teaching Assembly by Demonstration Using Advanced Human Robot Interaction and a Knowledge Integration Framework. Procedia Manufacturing. 11. 164–173. 23 indexed citations
12.
Bekiroglu, Yasemin, Andreas Damianou, Renaud Detry, et al.. (2016). Probabilistic consolidation of grasp experience. Explore Bristol Research. 193–200. 9 indexed citations
13.
Bekiroglu, Yasemin, et al.. (2016). Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces. arXiv (Cornell University). 582–589. 20 indexed citations
14.
Hang, Kaiyu, Miao Li, Johannes A. Stork, et al.. (2014). Hierarchical Fingertip Space for Synthesizing Adaptable Fingertip Grasps. Chalmers Research (Chalmers University of Technology). 2 indexed citations
15.
Bekiroglu, Yasemin, et al.. (2014). What's in the container? Classifying object contents from vision and touch. Chalmers Research (Chalmers University of Technology). 37 indexed citations
16.
Pokorny, Florian T., et al.. (2014). Grasp Moduli Spaces, Gaussian Processes and Multimodal Sensor Data. Chalmers Research (Chalmers University of Technology). 1 indexed citations
17.
Bekiroglu, Yasemin, Renaud Detry, & Danica Kragić. (2012). Grasp Stability from Vision and Touch. Open Repository and Bibliography (University of Liège). 1 indexed citations
18.
Bekiroglu, Yasemin, Renaud Detry, & Danica Kragić. (2011). Joint Observation of Object Pose and Tactile Imprints for Online Grasp Stability Assessment. Open Repository and Bibliography (University of Liège). 1 indexed citations
19.
Bekiroglu, Yasemin, Kai Huebner, & Danica Kragić. (2011). Integrating grasp planning with online stability assessment using tactile sensing. Chalmers Research (Chalmers University of Technology). 4750–4755. 12 indexed citations
20.
Bekiroglu, Yasemin, Ville Kyrki, & Danica Kragić. (2010). Learning grasp stability with tactile data and HMMs. Chalmers Research (Chalmers University of Technology).

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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