Jian Yao, born in December 1975, is from Lianyuan City, Hunan Province, China. Yao is a professor, Doctoral Supervisor, Distinguished Professor of "Chutian Scholar" Program of Hubei Province, Discipline Development Leader of the School of Remote Sensing Information Engineering of Wuhan University, a candidate of the National Major Talent Project A-type Youth Project, a member of the Strategic Talent Training Program of Changsha, a high-end talent of the 3551 Entrepreneurship and Innovation Program of Wuhan, a student of the Class 2019 of Baidu Alpha College, a leader of the Artificial Intelligence College of Guangdong Open University, director of the Artificial Intelligence Application Innovation Center of Guangdong Open University, dean of Research Institute of Desauto Technology (Shenzhen) Co., Ltd., Professor of Xiamen University of Aeronautics and Astronautics, distinguished researcher of Songhua River Thousand People Industry Research Institute, director of Wuhan University Computer Vision and Remote Sensing Lab (WHU-CVRS Lab), director of 3D Big Data Artificial Intelligence Innovation Research Center of Wuhan University, incumbent Member of the Chinese Society of Artificial Intelligence, member of the Computer Vision Professional Committee of the Chinese Computer Society (CCF), member of the Imaging Detection and Perception Committee of the Chinese Society of Image and Graphics, member of the Machine Vision Specialty Committee of the Chinese Society of Image and Graphics, member of 3D Vision Specialist Committee of the Chinese Society of Image and Graphics, member of the Big Data and Artificial Intelligence Working Committee of the Chinese Society of Surveying and Mapping, and director of the New Overseas Chinese Professionals Association of Hubei Province and Wuhan City. In April 2012, he was introduced to the School of Remote Sensing and Information Engineering of Wuhan University as a discipline development leader and has been a faculty member since then. He was invited as a specially-appointed professor of “Hubei Scholar” Program of Hubei in 2013. He has participated in many large-scale projects such as the EU's sixth and seventh framework plans, as well as cooperation projects with the International Atomic Energy Agency. In recent years, he has published over 130 papers on international journals including Pattern Recognition, Computer Vision & Image Understanding, International Journal of Robotics Research, IEEE Transactions on Image Processing, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing (TGRS) and CVPR, applied for over 70 IPs and patents, with 30 authorized by the Chinese government. He has long been a reviewer of top journals and conference proceedings. After joining Wuhan University, Prof. Yao has established the WHU-CVRS Lab, which now consists of four advisors, one postdoctoral fellows, 30 PhDs and master students. Prof. Yao has chaired a series of research projects at national and provincial levels, including national key research programs, programs of the 973 Project, and the National Natural Science Fund. Meanwhile, in collaboration with well-known enterprises like Tencent, Huawei and Alibaba, he has initiated a range of joint research programs and talent training projects. 

Title: AI + Intelligent Mobile Platform Technology and Application
Abstract: The mobile platform equipped with multiple sensors and AI engines to intelligently perceive 3D scenes, facilitate applications such as home services, education, medical care, express distribution, catering, and national defense. This is a hot topic both in current academic and industrial field. And it is also a trend of the future. The multi-sensors carried by the mobile platform includes LiDAR, IMU, RGBD camera, RGB camera, etc. The related AI technologies include object recognition, scene understanding, prediction, camera pose estimation, path planning and obstacle avoidance, 3D reconstruction, motion control, etc. The core technology of the AI+ intelligent mobile platform is constructing 3D semantic maps. 3D semantic maps provide a universal, large-scale, high-precision 3D representation and semantic map for various large-scale robots and mobile smart devices, so that robots and smart devices can position, path plan, avoid obstacles, and search object in non-visible areas automatically. This report will also introduce several AI+ intelligent mobile robots developed by our team, including intelligent bridge crack detection robots, inspection robots, smart helmets, and smart parking robots, etc. These has been successful applied in industry.