Ming Xiao

Ming Xiao's research is dedicated to advancing theories and methods for efficient information transmission and analysis across networks like 5G/6G and the Internet, vital for today's society. Aside from harsh conditions in real-life environments, other challenges for reliable transmission include the demand on higher data rates and quicker response times in modern applications such as 3D video, smart factories, and autonomous driving. Another challenge is the increase in data volume and computing devices (such as in large language models), which complicates network learning with issues like slow response, security risks, and high communication costs.

To overcome these obstacles, Xiao and his team have focused on using high-frequency bands to boost data rates and decrease latency. They have also investigated error-control and network coding to address transmission errors and enhance the responsiveness of learning devices. Moreover, they have developed distributed learning algorithms to improve learning speeds and secure the learning process. Through these efforts, Xiao's team aims to make information transmission quicker and more reliable, and network-based learning more efficient and secure, streamlining and safeguarding data usage in our increasingly connected world.