Papers

4

Total Citations

55

H-Index

3

About

Albert Wilcox is a robotics researcher whose work centers on imitation learning, model-based control, and surgical automation. He is best known for his pioneering contributions to robotic suturing, where he developed methods for autonomous localization, grasping, and handover of unmodified surgical needles—a critical step toward reducing surgeon fatigue during lengthy procedures. His paper on this topic has garnered 30 citations, reflecting its impact on the field of robotic surgical assistants. Wilcox also advanced interactive imitation learning with ThriftyDAgger, a budget-aware framework that intelligently gates human interventions to minimize burden while maximizing learning efficiency (19 citations). In model-based reinforcement learning, he tackled the challenge of accurate long-term dynamics prediction, enabling more reliable control for robotic systems. Earlier in his career, he explored internet-based control architectures for multiple co-operating robots, demonstrating his breadth of interest in autonomous systems. Wilcox’s work bridges practical surgical needs with foundational advances in robot learning, making him a notable figure in contemporary robotics research.

Research Focus

Key Achievements

3
H-Index
4
Papers
55
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Learning to Localize, Grasp, and Hand Over Unmodified Surgical Needles
30 citations · 2022
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Baton Rouge Clinic, University of California, Berkeley, Bournville College

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago