Joris De Winter
Papers
12
Total Citations
219
H-Index
7
About
Joris De Winter is a leading researcher at the intersection of human-robot collaboration (HRC) and intelligent manufacturing, with a focus on making robots safer, more intuitive, and more effective partners for humans. His work spans ergonomic task allocation, soft robotic interfaces, and reinforcement learning for autonomous assembly, addressing critical challenges in both industrial and rehabilitation settings. De Winter’s most cited paper, “Task allocation for improved ergonomics in Human-Robot Collaborative Assembly” (84 citations), pioneers methods to optimize human-robot teamwork in manufacturing, reducing physical strain while boosting efficiency. He further advances physical HRC by investigating strapping pressure dynamics in soft robotic cuffs (45 citations), enhancing comfort and power transfer in exoskeletons. His research on multi-modal social cues (19 citations) and transparent interaction-based learning (11 citations) pushes the boundaries of natural, adaptive collaboration. De Winter also contributes to robot-aided rehabilitation, promoting active patient participation through machine learning and impedance control (7 citations). With over 215 total citations and a growing portfolio of high-impact work, he is shaping the future of collaborative robotics—from factory floors to therapy clinics—by blending technical rigor with human-centered design.
Research Focus
Key Achievements
Top Papers
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- 6Transparent Interaction Based Learning for Human-Robot Collaboration11 citations · 2022
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- 10A muscle synergy-based method to improve robot-assisted movements3 citations · 2025