Adel Baselizadeh
Papers
7
Total Citations
51
H-Index
5
About
Adel Baselizadeh is a robotics researcher whose work sits at the intersection of human-robot interaction, motion planning, and privacy-preserving sensing. His primary research areas include safe robot manipulation, care robotics, and intuitive human-robot communication. Baselizadeh’s major contributions include developing a Nonlinear Model Predictive Control-based Reinforcement Learning framework for motion planning and obstacle avoidance in robot manipulators, which addresses critical safety challenges in dynamic environments. He has also pioneered privacy-preserving approaches for human-robot interaction, introducing methods that use local data processing and privacy-aware sensors to protect user data while maintaining system effectiveness. His work on the PriMA-Care dataset, a privacy-preserving multi-modal dataset for human activity recognition in care robots, has garnered significant attention with 9 citations. Additionally, Baselizadeh has explored the social dimensions of robotics, studying senior adults’ intuitive reactions to robot handshakes and how congruent robot speech and gestures enhance human understanding of robot intentions. With papers accumulating citations in the range of 3 to 10, his research is increasingly recognized for its practical implications in healthcare and assistive robotics, particularly in balancing utility and privacy in care settings.
Research Focus
Key Achievements
Top Papers
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- 6Using robotic mechanical perturbations for enhanced balance assessment5 citations · 2020
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