Long Xiangyun, male, born in 1988, is an associate professor at the School of Mechanical and Traffic Engineering, Hunan University. He has been engaged in intelligent damage assessment, machine vision, deep learning and digital twinning, and anti-damage design of aviation parts for a long time. The main research directions include intelligent damage perception, damage assessment based on machine vision and deep learning, anti-damage design of aero-engine structure, reliability theory and method, etc. In recent years, he has presided over 2 projects of National Natural Science Foundation, 1 National Boxing Plan, 1 China Aviation Cooperation Project and 1 Provincial and Ministerial Projects, and participated as a key member in topics such as nuclear science challenges in national defense basic research, major projects of National Natural Science Foundation, and aero-engine cooperation projects. He was selected into the National Postdoctoral Innovative Talents Program and the Young Teachers Support Program of Hunan University, the young editorial board of Journal of Hunan University (Natural Science Edition), and the backbone member of the national defense science and technology innovation team of special equipment reliability technology. The research results were published in important international academic journals such as Computer Methods in Applied Medicine, AIAA Daily and Engineering Fracture. At present, more than 30 papers have been published, 4 national invention patents have been applied for or authorized, 7 software copyrights have been granted, and 4 reports have been invited.