讲座人：
Yunjie Yang is the Lecturer (Assistant Professor) and Chancellor’s Fellow in Data Driven Innovation at the School of Engineering, The University of Edinburgh (UoE), UK. He received his B.Eng., M.Sc., and Ph.D. degrees from Anhui University, Tsinghua University, and The University of Edinburgh. He briefly worked as a Postdoctoral Research Associate in Chemical Species Tomography at UoE and then was appointed as the Lecturer and Chancellor's Fellow in Data Driven Innovation, where he established and led the SMART research group. His research interests are in the areas of sensing and imaging for medical, robotics, and energy engineering, and machine learning in inverse problems.
His research has led to over 90 high-impact journal and conference publications and has been funded by EU H2020, Data Driven Innovation Program, Wellcome Trust, and multiple industry funders. He serves as the Associate Editor of IEEE Transactions on Instrumentation and Measurement, IEEE Access, Frontiers in Electornics, and the Guest Editor of IEEE Sensors Journal and Chemosensors. He is the recipient of the 2015 IEEE I&M Society Graduate Fellowship Award and several best paper/poster awards.
讲座简介：
Natural creatures can accurately perceive their posture, position, movement, and environmental stimuli, yet this remains a fundamental challenge for bio-inspired soft robots. Gaining lifelike perception is fundamental to achieving precise control and robot-environment interaction, unlocking the full potential of soft robots and thus facilitating their widespread adoption in socially important areas such as healthcare and assisted living. This talk will introduce the recent research of Dr Yang’s group in flexible tomography for ultra-high-resolution soft robot perception, including tomography–inspired, stretchable 'e-skins', field-coupling e-skin-robot simulation, and machine learning-based e-skin data-to-perception translation algorithms.
讲座时间：2022年10月27日 16：00-17：00 北京
#腾讯会议：543-857-867
会议链接:https://meeting.tencent.com/dm/RkhmDGfJpdev
