Carlos Rossa
University of Alberta, Ontario Tech University, Carleton University
Papers
32
Total Citations
682
H-Index
16
About
Carlos Rossa is a prominent researcher specializing in medical robotics, needle steering mechanics, and surgical simulation, with a particular focus on improving the precision and safety of percutaneous interventions. His most celebrated contributions center on developing sophisticated dynamical models for flexible needle behavior in soft biological tissue. Notably, his 2016 work introduced the first model capable of simultaneously predicting both needle shape and tip position during robotic insertion — a landmark achievement that garnered 73 citations. His complementary investigations into tissue-cutting mechanics and needle-tissue interaction dynamics have further advanced the theoretical foundations of robot-assisted surgery, collectively attracting over 170 citations across related publications. Rossa has also made significant practical contributions, developing novel notched steerable needles capable of navigating around anatomical obstacles and pioneering ultrasound-based methods for real-time 3D needle shape reconstruction from 2D images — critical tools for clinical guidance systems. His 2017 review of closed-loop needle steering, his most cited work with 102 citations, synthesizes the field's challenges and directions comprehensively. More recently, his work evaluating virtual reality surgical simulators for nephrolithotomy training underscores his broadening commitment to medical education technology. Rossa's research sits at a compelling intersection of biomechanics, control systems, and clinical application.
Research Focus
Key Achievements
Top Papers
- 1Issues in closed-loop needle steering102 citations · 2017
- 2A Two-Body Rigid/Flexible Model of Needle Steering Dynamics in Soft Tissue73 citations · 2016
- 3Mechanics of Tissue Cutting During Needle Insertion in Biological Tissue71 citations · 2016
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