Daniel S. da Silva
Papers
1
Total Citations
13
H-Index
1
About
Daniel S. da Silva is a leading researcher at the intersection of robotics, machine learning, and surgical automation, with a primary focus on robot-assisted minimally invasive surgery (RMIS). His work addresses the critical challenge of enabling robots to learn complex surgical skills under the constraints of remote center of motion (RCM)—a fundamental requirement for safe and effective minimally invasive procedures. In his most-cited paper, "Learning surgical skills under the RCM constraint from demonstrations in robot-assisted minimally invasive surgery" (2023, 13 citations), da Silva pioneers a framework that allows surgical robots to acquire dexterous manipulation skills directly from human demonstrations while respecting the kinematic and safety constraints of RCM. This contribution is pivotal for advancing autonomous and semi-autonomous surgical systems, reducing the burden on surgeons, and improving procedural consistency. Beyond this landmark study, da Silva’s research spans imitation learning, constraint-aware motion planning, and human-robot interaction in medical contexts. His work has been recognized for its potential to transform surgical training and robot autonomy, making him a rising voice in the field of medical robotics.
Research Focus
Key Achievements
Top Papers
- 1