We conduct research in developing smart technology that can solve contemporary social problems of our daily life to achieve a better living for community.

The group’s major strength is Artificial Intelligence (AI) that can use machine comprehension to extract semantic meaning. Our application areas include cyber security, healthcare, smart city, tourism and domestic violence.

 

Areas of research

Research conducted in the areas of social good are:

  • domestic violence
  • digital abuse
  • machine emotion comprehension
  • AI for higher education
  • various AI applications in audio and video processing.

Research projects

  • Sentimental analysis and index of domestic violence through social media data analysis
  • Extracting actionable knowledge from domestic violence discourse on social media during COVID-19
  • Deep learning for domestic violence crisis identification from social media posts
  • Automatic identification of abuse and health mentions from online domestic violence posts using deep learning
  • Multimodal emotion detection using deep learning
  • Educational DSS (decision support system) using machine learning.

 

Research concentrated into the area of sustainable living and related applications are:

  • planetary health research
  • smart city research
  • digital construction.

Research projects

  • Footscray Smart City Social Cohesion project
  • Predicting car park occupancy rate in smart cities: A case study in Maribyrnong Council
  • City memory of Footscray (Maribyrnong, Victoria) Smart City
  • Machine comprehension for digitalised data.

 

Research conducted in the areas of cyber security and network intelligence are:

  • application & network security
  • cryptography and data privacy
  • edge computing & AI
  • WSN/IoT/WBAN.

Research projects

  • phishing detection using NLP and deep learning
  • storytelling with explainable AI for cyber security in partnership with Data61
  • TIDS: Trust Value Based IDS Framework for wireless body area network
  • using contemporary news sentiment with historical trade data to predict future price trends of a cryptocurrency
  • semantic analysis of transactions for anti money laundering
  • knowledge graph based blockchain technology.

Research conducted in the areas of health intelligence are:

  • aged care
  • mental health
  • effective and efficient health management.

Research projects

  • knowledge base construction for aged people nutrition with natural language processing
  • early depression detection with chat bot
  • solving dynamic patient admission scheduling problems
  • intelligent support to crypto library application in electronic medical record systems.

Researchers

Find out about our researchers, and access their biographies via the links.

  • Mrs Kiran Fahd
  • Mr Hamzah Hadi O Masmali
  • Mr Heerbod
  • Mr Payam Kaywan
  • Mr Reza Nowrozy
  • Mr Wimal Perera
  • Mrs Khadija Sultana
  • Mr Mohammad Yaghoubi.

 

Research publications

Members of ITIL group continue to publish their work in a broad range of scholarly journals and in proceedings of international learned conferences.

Check out their biographies to see their research publications.

Contact us

Professor Yuan Miao
Group Leader
Phone: +61 3 9919 4605 
Email[email protected].

Dr Khandakar Ahmed
Coordinator
Phone: +61 3 9919 6312
Email[email protected].