Gabriel Deza

University of California, Berkeley

Papers

2

Total Citations

21

H-Index

2

About

Gabriel Deza is a robotics researcher whose work centers on autonomous fabric manipulation and cloud-based robotic systems—a challenging intersection of perception, control, and remote operation. His most cited paper, "Learning to Fold Real Garments with One Arm: A Case Study in Cloud-Based Robotics Research" (2022, 19 citations), tackles the longstanding problem of deformable object handling. Deza’s key contribution is demonstrating that complex fabric folding can be achieved with a single robotic arm, a task traditionally requiring dual-arm setups. More importantly, he leverages the Reach cloud robotics platform to enable low-latency, remote execution of control policies on physical hardware, addressing the critical barrier of hardware cost and diversity that has hindered reproducible progress in the field. This work not only advances practical garment-folding capabilities but also provides a scalable framework for cloud-based robotics research, allowing other labs to test algorithms without owning expensive robots. Deza’s research thus bridges simulation and real-world deployment, offering a blueprint for democratizing access to physical robot experimentation. His findings have implications for manufacturing, healthcare, and domestic automation, where handling soft, deformable materials remains a frontier challenge.

Research Focus

Key Achievements

2
H-Index
2
Papers
21
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Learning to Fold Real Garments with One Arm: A Case Study in Cloud-Based Robotics Research
19 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago