Jialu Geng
Papers
3
Total Citations
80
H-Index
3
About
Jialu Geng is pioneering the future of robotic touch with groundbreaking work in flexible tactile sensing and electrical impedance tomography (EIT). Her research centers on developing large-area, skin-like sensors that overcome the limitations of traditional rigid arrays, enabling robots to perceive touch with unprecedented flexibility and scalability. Geng’s major contributions include the design of a large-area flexible tactile sensor for multi-touch and force detection using EIT, which has garnered 63 citations for its innovative approach to eliminating bulky wires and rigid components. She further advanced the field with a skin-like hydrogel sensor employing an EIT-based pseudo-array method (13 citations), demonstrating how compliant biomaterials can mimic human skin for distributed force sensing. To address the challenge of poor-quality reconstruction in EIT, Geng developed a convolutional neural network-based method (4 citations) that dramatically improves sensing accuracy. Her work is not only highly cited but also represents a critical step toward truly lifelike robotic skin, with potential applications in prosthetics, human-robot interaction, and soft robotics. Geng’s research stands at the intersection of materials science, sensor engineering, and machine learning, making her a rising leader in tactile sensing innovation.
Research Focus
Key Achievements
Top Papers
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