Nhan Huu Nguyen has been working as a postdoctoral researcher in Soft Haptics Labs, Japan Advanced Institute of Science and Technology (JAIST), Japan where he received the Ph.D. degree in robotics. He received his bachelor and master degrees in mechanical engineering at The University of Da Nang - University of Science and Technology (Viet Nam - 2015) and Ming Chi University of Science and Technology (Taiwan - 2017). His research focuses on exploiting complex physical interaction between deformable robots and the surrounding environment to enable novel functionalities such as tactile sensing, v.v., or facilitate learning and controlling tasks.

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Qiukai Qi is a Research Associate based in the Soft Robotics group at Bristol Robotics Laboratory. Prior to this position, he was a JSPS postdoctoral researcher at the Suzumori Laboratory at Tokyo Institute of Technology and a JSPS PhD research fellow at Soft Haptics Laboratory at Japan Advanced Institute of Science and Technology. Often inspired by biology, Qiukai aims to develop intelligent, autonomous, and adaptive soft robots that are safer to interact with or to function within humans and are “green” to environment. He is particularly interested in developing smart transducers using soft materials and structures, adaptive morphology, and artificial intelligence. Qiukai has a background in Mechanical Engineering (BEng), Robotics (MSc), and Information Science (PhD). 

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Helmut Hauser is a Senior Lecturer (Associate Professor) in Robotics at the University of Bristol and the Bristol Robotics Laboratory. Helmut is the Director of the EPSRC Centre of Doctoral Training for Robotics and Autonomous Systems (FARSCOPE TU). He also leads the UK-RAS Strategic Task Group for Soft Robotics, which promotes Soft Robotics in the UK. Helmut’s research is focused on morphological computation and embodiment, especially in the context of soft robotics. He is interested in understanding the underlying principles of how complex physical properties of biological systems are exploited to facilitate learning and controlling tasks, and how these principles can be employed to design better robots.  

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