Group Description:

The Intelligent Systems Research Group aims to bridge the gap between the research community and the industry community and to bring the most brilliant research ideas to solve real-world challenges.

The group currently has one research director, one associate director on advisory board,ten program leaders, and ten PhD and master of research students. Their research topics are: “Trustworthy AI-human interaction in cyber-physical systems”, “Privacy-preserving for intelligently connected vehicles”, “Detecting anomaly behaviour of elderly people using non-intrusive sensor fusion”, “Securing LiDAR based on autonomous driving systems”, “Leveraging data-driven metamorphic testing to improve robustness of DNNs”, and “Real-time anomaly detection of autonomous systems using online learners”.

The group has several projects in the past three years that addressed major issues in autonomous systems: “Dynamic Safety Analysis for Cyber-Physical Systems” ($18,000 AUD), and industry projects related to edge computing and micro-services “Customizable and efficient development and deployment of micro-service”($120,000 AUD), and awarded 2020 Australian Data61/CSIRO CRP Project “Trustworthy AI-human interaction in cyber-physical systems” ($130,440 AUD) (LEAD CI), and awarded 2020 Australian Research Council Linkage Project “A Safety-Preserving ecosystem for autonomous driving” ($341,853 AUD) (LEAD CI), and awarded 2021 Australian Research Council Discovery Project “Context-aware verification and validation framework for autonomous driving” ($448,958 AUD), and awarded Excellence in Early Career Research Award – Highly Commended, Faculty of Science and Engineering, Macquarie University.

The group’s recent paper “A survey on security issues in services communication of microservices-enabled fog applications” has been recognized as a top 20 most read paper (2017-2018) in Concurrency and Computation: Practice and Experience.

Selected work with real-world impact:

This paper is the first of its kind to use feature engineering and machine learning to solve a fundamental challenge in electric vehicles, which is to extend the mileage sustainable by in-car battery before requiring a recharge. The first author was a PhD student co-supervised by Dr Zheng in Tsinghua. With this work as one of the foundation, after graduation, the student was engaged by some venture capitals to establish a company producing electric vehicle power system. The experience gained from the work will aid Dr Zheng to resolve the machine learning related challenges in the real-world.

This paper is a pioneer to apply machine learning and feature engineering inside Alibaba Group to determine lucky money for online customers in “Double 11 Global Shopping Festival 2017”. The feature engineering part is very thoroughly conducted and with the evaluation of a few hundred million customers. The approach significantly reduces the campaign cost and boosts online sales. The first author has been working very closely with Dr Zheng on the solution and has been promoted to senior management role due to the outstanding contribution made through this work. The experience gained from feature engineering and machine learning will also help Dr Zheng to resolve machine learning-related challenges in the real-world.

Something New:

Important notice for PhD and MRes applicants: you need to have 6.5 out of 7 of your master degree in the MQ GPA rating system to be considered for PhD scholarship. An exception can be made for strong applicants who have been working with me side by side for top journals/conferences or having extensive research and industry experience. The interview is mandatory for all applicants. Be sure to include “apply for ISRG PhD or MRes” in your email subject line to avoid being ignored.

Latest Highly Cited Paper:
Professional activities
  • Distinguished Professor at Donghua University, China
  • Invited speaker for 2nd TECH.AD CHINA  https://www.autonomous-driving-china.com/
  • PC for IEEE International Conference on Trust, Security and Privacy in Computing and Communications 2020 (core A)
Awards:

Top Downloaded Article 2017-2018

Leading Publications 2018-2019 (Q1, SCI 1区-2区)

Partner Organizations:

Partner Universities: