Serge Garbay
Papers
1
Total Citations
2
H-Index
1
About
Serge Garbay is a researcher at the intersection of human-robot interaction, mixed reality, and machine learning, with a particular focus on intention estimation and haptic feedback systems. His work addresses the critical challenge of enabling robots and virtual environments to anticipate human actions in real time, a capability essential for collaborative manufacturing, prosthetics, and encountered-type haptics. Garbay’s most-cited paper, "Intention Estimation with Recurrent Neural Networks for Mixed Reality Environments" (2023), introduces a learning-based approach that outperforms traditional handcrafted feature methods by leveraging RNNs to model sequential human motion data. This contribution bridges the gap between heuristic intention models and modern deep learning, offering a scalable framework for adaptive human-robot collaboration. While his citation count is still growing—reflecting the recency of his work—Garbay’s research is positioned to influence next-generation assistive technologies and immersive interfaces. His focus on real-time, data-driven intention estimation marks him as an emerging voice in the field, with potential applications ranging from safer industrial cobots to more intuitive prosthetic control.
Research Focus
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Top Papers
- 1