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Professor Jiong Jin

Ph.D. in Engineering, The University of Melbourne, Australia; Bachelor of Engineering, Nanyang Technological University, Singapore


Dr. Jiong Jin is a full Professor and Academic Director (Research Training) in the School of Science, Computing and Engineering Technologies, Swinburne University of Technology. He received the B.Eng degree with First Class Honours in Computer Engineering from Nanyang Technological University, Singapore, in 2006, and the Ph.D. degree from the University of Melbourne, Australia, in 2011. Before joining Swinburne, Jiong was a Research Fellow in the Department of Electrical and Electronic Engineering, The University of Melbourne, from 2011 to 2013, where he was also affiliated with ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). The research focus of Jiong is on control and optimization of networked and embedded systems such as Internet of Things (IoT) and networked robotics. More specifically, his research interests include network design and optimization, edge computing and networking, robotics and automation, and cyber-physical systems and Internet of Things as well as their applications in smart manufacturing, smart transportation and smart cities. The goal of his research is to develop foundational theories and tools for concrete understanding and modelling of network system dynamics, to design scalable architecture and distributed algorithms for better performance, efficiency and robustness, and to further provide predictions that can be quantitatively verified by empirical data.

Research interests

Internet of Things; Network Optimization; Networked Robotics; Edge Computing; Industry 4.0

PhD candidate and honours supervision

Higher degrees by research

Accredited to supervise Masters & Doctoral students as Principal Supervisor.

PhD topics and outlines

Cloud Networked Robotics: Cloud Robotics is a new yet exciting field that deals with the concept of a network of robots leveraging ubiquitous cloud for collective intelligence. Diverse applications are now being proposed to utilize the benefit of cloud services for robotic networks. A typical example is “Noise Patrol Robots” that assist to better deal with urban noise problem in the smart city domain.

Distributed and Stochastic Network Optimization: Optimization theory has been widely applied to communication networks and become an essential modeling language and design method. We are interested in this project to develop distributed and/or stochastic optimization algorithms for diverse networking problems such as congestion control, resource allocation and cross-layer design.

Real-Time Internet of Things: The Internet of things (IoT) is an emerging revolution, which targets anytime connectivity for anything to create smart environments in which there is fast-paced interaction between systems and between such systems and people. The project aims to develop a flexible software-defined IoT platform to provide real-time services for smart city applications.

Wireless Robotic Networks: With the advance of M2M communications, wireless robotic networks can be formed to handle more complex and time-critical tasks in a distributed and parallel manner. The project aims to address 1) controllable mobility to enhance cross-layer optimization of communication protocols; 2) M2M to support dynamic resource management and self-organization for a team of cooperative robots.


Available to supervise honours students.

Fields of Research

  • Network Engineering - 400604
  • Cyberphysical Systems And Internet Of Things - 460603
  • Intelligent Robotics - 460205


  • 2022, International, AI 2000 Most Influential Scholars List as an Honourable Mention in the field of Internet of Things (ranked globally Top 100), AMiner
  • 2021, International, AI 2000 Most Influential Scholars List as an Honourable Mention in the field of Internet of Things (ranked globally Top 100), AMiner
  • 2020, Swinburne, School Research Excellence Award, School of Software and Electrical Engineering
  • 2019, Swinburne, Faculty Mid Career Researcher Award Commendation, Faculty of Science, Engineering and Technology


Also published as: Jin, Jiong; Jin, J.
This publication listing is provided by Swinburne Research Bank. If you are the owner of this profile, you can update your publications using our online form.

Recent research grants awarded

  • 2024: AI-Empowered Time Series Forecasting of User Electricity Consumption *; YSTC ENERGY PTY LTD FUND SCHEME
  • 2024: CSIRO - 61-NGET-R2 - Artificial Intelligence of Things Empowering Industrial Digital Twin *; Next Generation Graduates Program
  • 2023: Artificial Intelligence of Things Empowering Industrial Digital Twin *; Next Generation Graduates Program
  • 2023: UAV based Precision Agriculture for Fresh Food Supply Chain in Infrastructureless Environment *; iMOVECRC
  • 2022: Data-integrated Visualization and Analytics (DiVA) Platform for Transport Emissions, Efficiency and Sustainability *; iMOVECRC
  • 2022: Industrial Internet-of-Things Solution for Real-time Product Quality Assessment *; Innovative Manufacturing CRC
  • 2022: Unmanned Aerial Vehicles for Warehouse Roof Inspection *; iMOVECRC
  • 2021: Autonomous Data Acquisition and Analytic Platform for Fresh Food Supply Chain *; iMOVECRC
  • 2021: Toward big data processing in the integrated satellite IoT system *; KDDI Research Inc Japan
  • 2020: Privacy-Preserving FogIS in Infrastructure-Deficient Environments *; ARC Linkage Projects Scheme
  • 2019: A novel virtual manufacturing system approach for integrated flexible low-cost manufacturing to enhance cost competitiveness, value differentiation and market focus *; Innovative Manufacturing CRC
  • 2019: Delivery Drone Operator Training using Virtual Reality System *; iMOVECRC
  • 2019: Performance Guarantees for Real-Time Internet of Things *; ARC Discovery Projects Scheme
  • 2019: UAV Delivery Learning using VR Training Simulated Data *; iMOVECRC
  • 2018: Data-Driven Real-Time Resource Allocation for Multi-Agent Cloud Robotics System- Student scholarship *; DATA61
  • 2014: Adaptive Quality of Service Mechanisms for Internet of Things. *; Early/Interrupted Research Career Scheme

* Chief Investigator

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