Data-Driven Methods for Sustainable Industrial and AIoT Systems

Conventional industrial systems and emerging systems such as data centers, 5G communication networks consume enormous amount of energy and non-renewable resources. We focus on developing advanced data-driven AI methods to optimize real-world complex industrial and AIoT systems. Helping the related industries to improve operation efficiency, save energy, reduce emission, and ultimately achieving the goal of green and sustanable development.

Our current research focus include:

  • Simulator-free data-driven control optimization for complex industrial systems
  • Energy saving optimization for data centers
  • 5G Massive MIMO Beamforming optimization
  • Engineering policy integrated hybrid RL
Xianyuan Zhan
Xianyuan Zhan
Faculty Member