معرفی
Xingyong Song is an Associate Professor at Texas A&M University's College of Engineering, affiliated with the Department of Engineering Technology and Industrial Distribution and Electrical & Computer Engineering. He holds a Ph.D. in Mechanical Engineering from the University of Minnesota (2011), and degrees from Korea Advanced Institute of Science and Technology and Harbin Institute of Technology. His research focuses on automation, machine learning, autonomous vehicles, and drilling automation. He leads the Controls and Mechatronics Research Lab, which explores machine intelligence, connected vehicles, and energy systems.
Key research projects include NSF-funded work on autonomous directional drilling and powertrain optimization for autonomous vehicles. His awards include the NSF CAREER Award (2021) and NAS GRP Early Career Award (2018). He advises multiple PhD and master’s students and has published extensively in top journals like IEEE Transactions and Automatica.
Dr. Song’s lab develops advanced control systems for oil/gas, automotive, and construction industries. His research spans optimal control, reinforcement learning, and mechatronics design. He collaborates with industry partners on projects like vision-based pipe inspection and catalyst filling automation.
