Papers
3
Total Citations
40
H-Index
3
About
P. Ganesh is a rising researcher at the intersection of haptic technology and robotic-assisted surgery, whose work is pioneering new methods for restoring the sense of touch in minimally invasive procedures. His primary research areas include force feedback estimation, deep learning for surgical robotics, and computer vision. Ganesh’s major contribution lies in developing data-driven neural network approaches—specifically recurrent and convolutional architectures—to reproduce and estimate variable visuo-haptic force feedback during surgical tool insertion. His 2023 paper on a recurrent neural network approach for force reproduction has garnered 17 citations, while his investigation into dimensionality reduction for force estimation using recurrent and convolutional networks has received 16 citations. In 2024, he advanced this field further with a stereovision-based method employing a Modified Inception ResNet V2 network to retrieve variable force feedback, demonstrating the potential to significantly improve surgeon experience in Robotic-Assisted Minimally Invasive Surgery (RAMIS). Ganesh’s work is critical for bridging the sensory gap in telesurgery, promising safer and more intuitive robotic operations.
Research Focus
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