Shuai Huang

Machine Learning, Healthcare, and Manufacturing


Shuai’s research is driven by challenging data analytics problems, emphasizes innovation in statistics for problem solving, and targets system-level decision making and quality improvement. He develops methodologies for modeling, monitoring, diagnosis, and prognosis of complex networked systems, such as brain connectivity networks, social networks, cyber-physics systems, and manufacturing systems. He also develops novel statistical and data mining models to integrate the massive heterogeneous datasets such as neuroimaging, genomics, proteomics, laboratory tests, demographics, and clinical variables, for facilitating scientific discoveries in biomedical research and better decision making in clinical practices.


Research Thrust 1: Basic Research towards Mechanistic Understanding of Complex System Problems


  • Brain connectivity modeling using Neuroimaging data (link)
  • Towards mechanistic understanding of type 1 diabetes (link)

Research Thrust 2: Translation of Mechanistic Understanding into Decision Making for Better System Management


  • Smart monitoring of complex diseases (link)
  • Integration with mHealth technology (link)

Research Thrust 3: Generalization of Different Applications into Holistic Methodologies of Data-Driven System Modeling, Monitoring, and Optimization


  • Network modeling & learning, monitoring & diagnosis, sensing & control (link)
  • High-dimensional statistical learning and data analysis (link)
  • Quality control of high-dimensional systems (link)
  • Prognostics and health management (link)