Centre for Big Data Analytics and Intelligent Systems (BDAIS)

Centre for Big Data Analytics and Intelligent Systems focuses on the theory development, novel techniques and smart solutions of big data analytics in broad domains, along with theories and techniques of building computer systems, which capture the intelligent behaviours in complex environments. The research interests of the centre include distributed artificial intelligence, collective intelligence in social systems, mechanism designs for big data analytics, the application of big data analytics in decision-making and problem solving, multi-agent technology and their applications, smart city and smart grid systems, smart modelling and simulations in complex systems, data mining, deep learning and knowledge discovery in broad domains, machine learning, and Internet of Things.

Theme & Goals

Theme

The theme of Centre for Big Data Analytics and Intelligent Systems, leading by Prof Minjie Zhang, is to develop smart solutions to computer-based systems and social systems that operate in complex environments. The centre aims to build a collaborative research team, which can contribute high quality research outcomes and impacts. The centre also aims to foster quality HDR students in the fields through co-supervision. 

Goals

Centre for Big Data Analytics and Intelligent Systems focuses on the theory development, novel techniques and smart solutions of big data analytics in broad domains, along with theories and techniques of building computer systems, which capture the intelligent behaviours in complex environments. The research interests of the centre include distributed artificial intelligence, collective intelligence in social systems, mechanism designs for big data analytics, the application of big data analytics in decision-making and problem solving, multi-agent technology and their applications, smart city and smart grid systems, smart modelling and simulations in complex systems, data mining, deep learning and knowledge discovery in broad domains, machine learning, and Internet of Things.


Research

Research topics

  • Collective intelligence in social systems and e-governments
  • Enhanced decision-making and problem-solving through the application of big data analytics in turbulent environments
  • Mechanism design and modelling for big data analysis
  • Foundation research in agent and multi-agent systems
  • Smart modelling and simulation for complex systems
  • Trust models and resource management in service oriented systems
  • Multi-agent solutions and social learning in market environments
  • Self-organization/coordination in competitive/collaboration environments
  • Smart cities, smart communities, and smart grid systems
  • Resource managements in grid/cloud/service oriented systems and disaster environments
  • Data mining, text data mining, deep learning and knowledge discovery in both computer based systems and social systems

Research projects

  • Resource managements in multiple emergency events
  • Concurrent and multiple negotiations among autonomous agents
  • Supply-demand balance in smart grid markets through customer behaviours learning
  • Multi-agent learning in complex environments
  • Privacy risk management and trust models in online social networks
  • Social norm emergence in local communities through deep learning Agent-assisted
  • Emergency evacuation modelling and simulation
  • Big data and big data analytics for agile on-demand services in government
  • Big data analytics use in open government data environments
  • Budget transparency through open government data analytics
  • Social media text analytics for double-loop learning for citizen-centric public services
  • Paths from open justice to e-justice
  • Temporal analysis of big data in Apache Spark
  • Self-adaptive software systems
  • Visual concept learning for intelligent semantic search for big data
  • Authorship attribution and topic discovery with data mining