David Hardman
Bridge University, University of Cambridge, Inspire Institute
Papers
14
Total Citations
272
H-Index
7
About
David Hardman is an emerging researcher whose work sits at the intersection of soft robotics, advanced materials, and tactile sensing. His research focuses on developing novel hydrogel-based sensing technologies, electrical impedance tomography (EIT) for robotic skins, and 3D-printable soft sensor systems that push the boundaries of what compliant robotic systems can perceive and achieve. Hardman's most influential contribution is his development of self-healing ionic gelatin/glycerol hydrogels for strain sensing, which has garnered 140 citations and demonstrated the transformative potential of soft materials in wearable devices and haptic interfaces. His broader body of work explores how hydrogels can be engineered into sophisticated multi-material structures, sensorized robotic skins, and soft sensory fiber networks, collectively accumulating over 200 citations across his career. Particularly noteworthy is his interdisciplinary reach: from biomimetic high-speed Braille reading pipelines and deep reinforcement learning for fluid-surface manipulation, to closed-loop morphological optimization of 3D-printed sensors. His 2025 survey on soft robot adaptability signals growing influence in shaping how the field conceptualizes intelligent, compliant systems. For students entering soft robotics or smart materials research, Hardman's work represents a compelling model of how materials science, sensing, and machine learning can be unified toward genuinely capable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Self-healing ionic gelatin/glycerol hydrogels for strain sensing applications140 citations · 2022
- 2
- 3
- 4
- 5High-Speed Tactile Braille Reading via Biomimetic Sliding Interactions9 citations · 2024
- 6
- 7
- 8
- 9
- 10