About

Yasemin Bekiroglu is a prominent robotics researcher whose work sits at the intersection of robotic manipulation, tactile sensing, and machine learning. Her research has fundamentally advanced how robots perceive, grasp, and interact with objects in uncertain, real-world environments. Bekiroglu's most influential contributions center on grasp stability assessment, where she pioneered learning-based methods that leverage haptic and tactile data to enable robots to evaluate and adapt their grasps in real time — work that has accumulated nearly 200 citations and reshaped thinking in robotic manipulation. Her investigations into tactile exploration for shape perception and object content classification further demonstrate her commitment to multimodal sensory integration, enabling robots to build richer environmental models from incomplete data. Bekiroglu has also made notable strides in dynamic grasping of moving objects and human-robot collaborative assembly, broadening the practical applicability of her research to industrial settings. Particularly noteworthy is her pilot work on autonomous robotic systems for nuclear decommissioning, addressing one of the most challenging and socially significant robotics deployment scenarios. With over 800 citations across her body of work, Bekiroglu stands as a leading voice in intelligent robotic manipulation research.

Research Focus

Key Achievements

15
H-Index
33
Papers
1,084
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
Assessing Grasp Stability Based on Learning and Haptic Data
189 citations · 2011
📈 Most Prolific Year: 2011 (5 Papers)
🤝 Key Collaborators: 72
🏛 Institutions: KTH Royal Institute of Technology, University of Birmingham, ABB (Sweden), University College London, Chalmers University of Technology, Max Planck Institute for Intelligent Systems

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago