Qiran Sun

Papers

Total Citations

H-Index

About

Qiran Sun is a researcher at the forefront of computational mechanics and haptic sensing, with a particular focus on integrating neural operators into physical interaction systems. Their most notable work, "Neural operator-based haptic sensing along slender rods" (2025), introduces a novel framework that leverages deep learning to model and interpret tactile feedback in flexible, rod-like structures—a breakthrough with implications for robotics, minimally invasive surgery, and soft material manipulation. This paper, already garnering 3 citations in its early publication stage, demonstrates Sun’s ability to bridge data-driven methods with classical mechanics, enabling real-time, high-fidelity sensing without exhaustive physical simulations. Sun’s contributions lie in advancing neural operator architectures to handle complex, continuous physical fields, offering a paradigm shift from traditional discrete sensing. Their work is particularly impactful for applications requiring precise haptic feedback in constrained environments, such as catheter steering or endoscopic tools. As an emerging voice in the field, Sun’s research promises to reshape how machines perceive and interact with deformable objects, making them a key figure to watch in the evolving landscape of embodied AI and computational sensing.