Zuogong Yue, Assistant Professor at School of Artificial Intelligence and Automation. His major interestes include network inference, system identification, signal processing and machine learning. He focuses on analysis methods and algorithms for sequential data or time series. He also gets involved in several applications to interdisciplinary research.

The ongoing projects:

• Network Reconstruction/Inference/Identification
  
  It mainly studies how to use dynamical system theory, system identification, and machine learning to solve network inference from time series. It aims to provide theoretical foundations for networked dynamical system modelling, analysis and control.
  
  

• Large-scale System Identification
  
  It focuses on using large-scale Bayesian learning for time series modelling. It also includes large-scale sparse learning problems, which play a critical role in methods for network inference.
  
  

• Unsupervised Learning for Sequential Data/Time Series
  
  Now mainly time-series clustering.
  
  

• And, interdisciplinary applications.