Gokhan Serhat
Papers
3
Total Citations
81
H-Index
3
About
Gokhan Serhat is a leading researcher in soft haptics and tactile sensing, whose work bridges the gap between flexible, wearable hardware and intelligent machine learning. His primary research areas include electrical resistance tomography (ERT)-based tactile sensors, soft robotic skin, and haptic feedback systems for human-computer interaction. Serhat’s major contributions lie in solving the ill-posed inverse problem of pressure reconstruction in ERT sensors. He pioneered the use of multiphysics simulation and sim-to-real transfer learning to calibrate these sensors, achieving robust force mapping without extensive physical data collection. His 2022 paper, "Predicting the Force Map of an ERT-Based Tactile Sensor Using Simulation and Deep Networks," has garnered 46 citations for its novel approach to creating fast, accurate mappings from voltage measurements to force distributions. Additionally, his work on generating clear vibrotactile cues using magnets embedded in soft finger sheaths (2022, 11 citations) demonstrates his commitment to making haptic displays lightweight, comfortable, and practical for applications ranging from rehabilitation to remote surgery. Serhat’s research is pivotal in advancing soft, scalable, and affordable tactile technologies for next-generation robotics and wearable devices.
Research Focus
Key Achievements
Top Papers
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