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Systems Analytics Laboratory (SAL)

Location:HW 1-2 - Upper floor


The mission of the Systems Analytics Lab (SAL) is to support teaching and research activities in systems analytics, one of the three pillars of the core competence of IMSE at HKU. The R&D at SAL also serves as enabling technologies for the other two pillars of the core competence, cyber-physical systems and supply chain management.

SAL aims to develop and apply data-driven quantitative methods to deliver solutions for decision-making problems in complex systems. Analytical modeling, powered by big data, is the core methodological foundation at SAL. The solution methodologies developed at SAL are computationally intensive and enabled by advanced industrial engineering techniques, including optimisation, high-dimensional statistics, stochastic modeling, artificial intelligence, machine learning, and systems simulation. SAL has successfully rolled out the R&D work for a wide range of applications in various industries, including construction, finance, healthcare, logistics and transportation, manufacturing, and supply chain management.

The facilities of SAL support the following courses offered by IMSE:

  • IMSE3107 Systems modelling and simulation
  • IMSE3111 Intelligent optimisation
  • IMSE3136 Operations planning and control
  • IMSE4122 Global logistics systems
  • IMSE4135 Systems integration
  • IMSE4136 Transportation and distribution planning
  • IMSE4174 Project
  • IMSE4175 Systems analytics and integration
  • IELM7015 Global logistics
  • IELM7023 Systems integration and analytics

In addition to off-the-shelf, state-of-the-art research tools equipped at SAL, the Lab also strives to develop industrial-based systems analytics technologies to conduct cutting-edge research and put them into implementation. The projects at SAL have been supported by multiple funding agencies, including Hong Kong Research Grants Council, Innovation and Technology Fund and Health and Medical Research Fund, and contract research in collaboration with key industrial parties.

If you are interested in joining SAL, please do not hesitate to contact our affiliated faculty members:

  • Dr. Peng-Chu Chen [javascript protected email address]
  • Dr. Yao Cheng [javascript protected email address]
  • Dr. Yong-Hong Kuo [javascript protected email address]
  • Dr. Junwei Wang [javascript protected email address]
  • Dr. Fangni Zhang [javascript protected email address]
  • Dr. Ray Y. Zhong [javascript protected email address]