Biography

 

Professor Yam is a Program Leader and Principal Investigator of the Centre for Perceptual and Interactive Intelligence (CPII), and a Principal Investigator of the Multi-Scale Medical Robotic Center (MRC). He also serves as the Director of the CUHK Shenzhen Research Institute, and the Principal Investigator of the CUHK Jockey Club AI for the Future Project on driving secondary school AI education in Hong Kong. Before joining CUHK, Professor Yam was with the Jet Propulsion Laboratory, Pasadena, CA, in USA.  His general research interests include intelligent systems, surgical robots, and human skill acquisition. He has published over 250 technical papers in his areas of interest. 

 

 

Topic: Fabrication and AI-enabled Applications of 3D-formed Composite Materials

 

A key objective in the research of AI-enabled personalized design and fabrication at CPII is the incorporation of novel materials to wearable fabrics for enhanced applications. Normal knitting process, with its characteristic loop structure, is limited for this purpose -- materials such as carbon fibre, for example, tend to break during the looping process or even damage the knitting machine due to their high stiffness. On the other hand, weaving can readily handle these materials because its stitching structure is basically composed of straight weft and warp threads. In this talk, we will introduce the development of a computer-controlled weaving machine prototype capable of incorporating non-traditional materials in the fabrics. The prototype is able to execute the 3D form fitting technology developed in our laboratory intended originally for knitting machines. So far, our weaving prototype has produced 3D fabrics embedding materials that include carbon fibres, optical fibres, and conductive threads. These the 3D-formed composite materials will have strong potential in fashion design, wearable devices and serving as touching/touchless sensors for close-proximity human-robot collaboration. Moving forward, AI-based techniques will be applied for enhanced interpretation of sensory signals from these 3D fabrics to facilitate their future applications.