Prof Wei Xiang ~ Adjunct Professor
Engineering
- About
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- Interests
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- Research
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- Wireless Communications
- Internet of Things
- Image and Video Communications
- Communications Theory
- Coding and Information Theory
- Wireless Sensor Networks
- Experience
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- 2016 to present - Foundation Professor and Head of Discipline Electronic Systems & Internet of Things Engineering, James Cook University (Cairns, Australia)
- 2015 - JSPS Invitational Professor, University of Tsukuba (Tsukuba, Japan)
- 2013 to 2015 - Associate Professor, University of Southern Queensland (Toowoomba, Australia)
- 2012 to 2013 - Endeavour Visiting Associate Professor, University of Hong Kong (Hong Kong, China)
- 2009 to 2012 - Senior Lecturer, University of Southern Queensland (Toowoomba, Australia)
- 2010 to 2011 - Visiting Scholar, University of Mississippi (Oxford, MS, USA)
- 2006 to 2009 - Principal Advisor (Research, 0.2 FTE), University of Southern Queensland (Toowoomba, Australia)
- 2008 - Visiting scholar, Nanyang Technological University (Singapore)
- 2004 to 2008 - Lecturer, University of Southern Queensland (Toowoomba, Australia)
- Research Disciplines
- Socio-Economic Objectives
Profile
Professor Wei Xiang is Founding Chair and Head of Discipline Electronic Systems and Internet of Things Engineering. He is an elected Fellow of the IET (FIET) and a Fellow of Engineers Australia (FIEAust).
He was responsible for establishing Australia's first Bachelor of Engineering major in Internet of Things Engineering, which was successfully acredited by Engineers Australia in November 2016. Due to his instrumental leadership in establishing Australia’s first accredited Internet of Things Engineering degree program, he was selected into Pearcy Foundation’s Hall of Fame in October 2018. He received the TNQ Innovation Award in 2016, and PearceyEntrepreneurship Award in 2017, and Engineers Australia Cairns Engineer of the Year in 2017. He was a co-recipient of four Best Paper Awards at WiSATS’2019, WCSP’2015, IEEE WCNC’2011, and ICWMC’2009. He has been awarded several prestigious fellowship titles. He has been named a Queensland International Fellow by the Queensland Government, an Endeavour Research Fellow by the Commonwealth Government of Australia, a Smart Futures Fellow by the Queensland Government, and a JSPS Invitational Fellow jointly by the Australian Academy of Science and Japanese Society for Promotion of Science (2014-2015). He is the Vice Chair of the IEEE Northern Australia Section. He was an Editor for IEEE Communications Letters (2015-2017), and is an Associate Editor for Springer’s Telecommunications Systems. He has published over 250 peer-reviewed papers including 3 academic books and 130 journal articles, six of which are ESI Top 1% Highly Cited papers. He has severed in a large number of international conferences in the capacity of General Co-Chair, TPC Co-Chair, Symposium Chair, etc.
His research areas include the Internet of Things, machine learning for the Internet of Things, machine learning for computer vision, and big IoT data analytics.
PhD Scholarship Opportunities
I am an experienced PhD supervisor, having graduated 12 PhD students as principal and co-supervisors. I am interested in receiving inquiries from prospective PhD and Masters by Research candidates, who are interested in the research areas of the Internet of Things (IoT), machine learning for IoT, machine learning for computer vision, etc. Scholarship funding is available through the Australian Postgraduate Awards (APA), the James Cook University Postgraduate Research Scholarships, the Australia Awards, and the Chinese Scholarship Council (CSC).
To apply for a JCU Competitive PhD Scholarship, here is How to Apply. Closing deadlines: 31 September 2019.
I am also supervising two postdoctoral research fellows. If you are a recent PhD graduate and want to pursue a postdoctoral fellowship, opportunities exist through the Australian Research Council (DECRA) and Endeavour Research Fellowship. Please contact me for details.
Publications
I have over 250 publicaitons in refereered journals and peer-reviewed conference proceedings. Most of them are published by the Institute of Electricla and Eletronics Engineers (IEEE), which represents the highest academic standards in the eletrical & eletronic, and telecommunications engineering disciplines. I have published extensively in some world's top-ranked journals in my areas such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Image Processing, IEEE Transactions on Wireless Communications, IEEE Journal of Selected Areas in Communications, etc. Moreover, six of my publications are rated by the Web of Science ESI (Essential Science Indicators) as Highly Cited Papers (top 1% citation in the chosen field).
You are welcom to follow my publications at the dblp computer science bibliography and ResearchGate.
- Honours
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- Awards
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- 2017 - Engineers Australia Cairns Regional Engineer of the Year
- 2017 - Pearcey QLD Entrepreneur Award (Highly Commended)
- 2016 - Tropical North Queensland Innovation Award
- 2015 - USQ Publication Excellence Award (1st Prize)
- 2015 - Best Paper Award, 7th International Conference on Wireless Communications and Signal Processing (WCSP’2015), Nanjing, China, Oct. 2015
- 2014 - USQ Publication Excellence Award (1st Prize)
- 2014 - Named by the Queensland Science Minster’s as one of the seven Queensland world-glass research leaders
- 2014 - USQ Excellence in Research Award (sole recipient in the open category)
- 2012 - Faculty Research Excellence Award, Faculty of Engineering, University of Southern Queensland
- 2012 - Endeavour Award, Australian Government Department of Education, Employment and Workplace Relations
- 2011 - Best Paper Award, IEEE Wireless Communications & Networking Conference (WCNC), 2011
- 2009 - Best Paper Award, ICWMC, 2009
- Fellowships
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- 2012 - Endeavour Research Fellow, Australian Government Department of Education, Employment and Workplace Relations
- 2011 - Queensland International Fellowship, Queensland Government of Australia
- 2012 to 2016 - Smart Futures Fellow (Mid-Career), Queensland Government of Australia
- 2015 - Tsinghua Global Scholars Fellow, Tsinghua University, China
- 2014 to 2015 - JSPS Invitational Fellow, Japanese Society for the Promotion of Science (JSPS)
- Memberships
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- 2016 - Fellow of Engineers Australia
- 2015 - Fellow of the Institution of Engineering and Technology (IET)
- 2008 - Senior Member of the Institute of Electrical and Electronics Engineers
- Other
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- 2017 - Vice Chair - IEEE Northern Australia Section
- 2016 - Theo Murphy High Flyers Think Tank Delegate, Australia Academy of Science
- Publications
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These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.
- Journal Articles
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- Ahmad J, Zia M, Naqvi I, Chattha J, Butt F, Huang T and Xiang W (in press) Machine learning and blockchain technologies for cybersecurity in connected vehicles. WIREs Data Mining and Knowledge Discovery,
- Baker S and Xiang W (2023) Artificial Intelligence of Things for Smarter Healthcare: A Survey of Advancements, Challenges, and Opportunities. IEEE Communications Surveys & Tutorials, 25 (2). pp. 1261-1293
- Haider M, Peyal M, Huang T and Xiang W (in press) Road crack avoidance: a convolutional neural network-based smart transportation system for intelligent vehicles. Journal of Intelligent Transportation Systems,
- Yang W, Xiang W, Yang Y and Cheng P (2023) Optimizing Federated Learning With Deep Reinforcement Learning for Digital Twin Empowered Industrial IoT. IEEE Transactions on Industrial Informatics, 19 (2). pp. 1884-1893
- Zhou X, Xiang W and Huang T (in press) A novel neural network for improved in-hospital mortality prediction with irregular and incomplete multivariate data. Neural Networks,
- Zia M, Xiang W, Vitetta G and Huang T (2023) Deep Learning for Parametric Channel Estimation in Massive MIMO Systems. IEEE Transactions on Vehicular Technology, 72 (4). pp. 4157 -4167
- Baker S, Xiang W and Atkinson I (2022) A computationally efficient CNN-LSTM neural network for estimation of blood pressure from features of electrocardiogram and photoplethysmogram waveforms. Knowledge Based Systems, 250.
- Fang J, Zhou K, Zhang M and Xiang W (2022) Resource Scheduling Strategy for Performance Optimization Based on Heterogeneous CPU-GPU Platform. Computers, Materials & Continua, 73 (1). pp. 1621-1635
- Fang J, Mao Y, Cai M, Zhao L, Chen H and Xiang W (2022) STTAR: A Traffic- and Thermal-Aware Adaptive Routing for 3D Network-on-Chip Systems. Computers, Materials & Continua, 72 (3). pp. 5531-5545
- Fu Y, Guo D, Li Q, Liu L, Qu S and Xiang W (2022) Digital Twin Based Network Latency Prediction in Vehicular Networks. Electronics, 11 (14).
- Fu Y, Du Y, Cao Z, Li Q and Xiang W (2022) A deep learning model for network intrusion detection with imbalanced data. Electronics, 11 (6).
- Book Chapters
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- Talkhani R, Huang T, Gu S, Guo Z, Zhang G and Xiang W (2023) Deep learning for vehicle safety. In: Deep Learning and Its Applications for Vehicle Networks. CRC Press, Boca Raton, FL, USA, pp. 3-16
- More
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ResearchOnline@JCU stores 283+ research outputs authored by Prof Wei Xiang from 2009 onwards.
- Current Funding
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Current and recent Research Funding to JCU is shown by funding source and project.
Australian Government Department of Agriculture, Water and the Environment - National Landcare Program: Smart Farming Partnerships Grant
Climate Smart Sugarcane Irrigation Partnerships (CSSIP)
- Indicative Funding
- $1,586,884 over 5 years
- Summary
- CSSIP will minimise nutrient runoff, improve soil health and increase wetlands water quality by facilitating the adoption of world-class irrigation practices in sugarcane farming systems. Currently, best practice irrigation is assisted by an Irrigation Decision Support Tool (IDST) that provides evidence-based advice. However, IDSTs have not reached their full potential. Firstly, they do not integrate short to medium term weather forecasts (e.g. weekly to multi-weekly forecasts). Secondly, IDSTs do not operate at a spatial scale relevant to farmers. CSSIP will incorporate the Bureau or Meteorology?s new high-resolution climate model into the Irrigation Decision Support Tool. Thirdly, IDSTs require substantial time in manual data entry, which can be alleviated using real-time monitoring via Internet of Things technologies. This will increase irrigation efficiency, reducing excessive runoff into river systems and onto the Reef, and, will help farmers save water and energy costs.
- Investigators
- Bronson Philippa, Yvette Everingham, Eric Wang, Stephen Attard and Wei Xiang in collaboration with Geoff Inman-Bamber, Marian Davis, Andrew Schepen, Brock Dembowski, Peter Larsen and Andres Jaramillo (College of Science & Engineering, AgriTech Solutions, Burdekin Productivity Services, Commonwealth Scientific & Industrial Research Organisation, Department of Agriculture and Fisheries, Wilmar Sugar Australia and Sugar Research Australia)
- Keywords
- Sugarcane; Internet of Things; Irrigation
Huawei Technologies (Australia) Pty Ltd - JCU-Enex NB-IoT Testing and Certification Centre
NB-IoT Testing and Certification
- Indicative Funding
- $109,092 over 4 years
- Summary
- Develop Narrowband Internet-of-Things (NB-IoT) testing methods and procedures for NB-IoT end-user terminals (devices) based on NB-IoT Release 13. This will involve detailed research, evaluation and development of processes and procedures for carrying out testing against the 3GPP standard for NB-IoT devices within a framework that enables formal certification under NATA rules; working with external partners towards carrying out an initial NB-IoT device 3GPP certification; and developing a business model and recommendations for the establishment of an NB-IoT Certification Centre.
- Investigators
- Wei Xiang in collaboration with Andrew Krockenberger (College of Science & Engineering and Research Infrastructure)
- Keywords
- Internet-of-Things (IoT); NB-IoT; Business Case; Testing; Certification; 3GPP
CRC for Developing Northern Australia Scheme - Projects
Applying new technologies to enhance biosecurity and cattle quality.
- Indicative Funding
- $1,084,500 over 3 years (administered by Branir Pty Ltd & Trustee for Booloomani Unit Trust)
- Summary
- The vast natural environment of Northern Australia feeds the cattle industry; however, biosecurity threats have negatively impacted this. Conventional management of such threats such as weeds are not suited to such broad, harsh landscapes. The project will use an Internet of Things network with low-cost environmental sensors, drone mapping and big data analytics to develop and test data-driven, strategic pest management programs - ultimately improving both cattle industry and natural assets.
- Investigators
- Ian Atkinson, Wei Xiang, Ron White, Stephanie Duce, Mohan Jacob and Karen Joyce (Research Infrastructure and College of Science & Engineering)
- Keywords
- Biosecurity; Cattle; Drones; Weeds; Technology; Internet Of Things
QLD Department of Science, Information Technology and Innovation - Advance Queensland Innovation Partnerships
Smart Ear Tag for Livestock
- Indicative Funding
- $1,500,000 over 4 years
- Summary
- CeresTag is investing in the development of a smart ear tag for livestock to enable near real-time geo-location and health monitoring. The developed ear tag will be compliant with the current NLIS identification system and cost only marginally more than existing tags. This technology will revolutionise the industry through enhanced animal welfare, improved land management practices and increased profitability. It will form the starting point of block chain traceability that will underpin the continued success of this important component of the Australian economy and help maintain the premium status of Australian livestock products.
- Investigators
- Ian Atkinson, Wei Xiang, Bronson Philippa, Ed Charmley, Greg Bishop-Hurley, Nigel Bajema, Scott Mills, Gordon Foyster and Richard Keaney (Research Infrastructure, College of Science & Engineering, Commonwealth Scientific & Industrial Research Organisation and Taggle Systems)
- Keywords
- Animal tracking; Internet Of Things; Microelectronics; Geo-location; Precision Agriculture; Beef Cattle
Huawei Technologies (Australia) Pty Ltd - Grant
Joint Huawei-JCU Internet of Things Laboratory
- Indicative Funding
- $100,000 over 5 years
- Summary
- To enable the collaboration on opportunities that include: a) establishing a joint Huawei-JCU Internet of Things (loT) Laboratory: b) use the joint loT Lab to promote strong academic-industry collaboration; leveraging on Australia's first loT Engineering degree program run by JCU etc.
- Investigators
- Wei Xiang (College of Science & Engineering)
- Keywords
- Narrowband (NB); Communication and information; Internet of Things
Department of Industry - Innovations Connections
Vibration analysis of mining industry conveyor belt systems: validation of method and pathways to improvement
- Indicative Funding
- $48,811 over 1 year, in partnership with Rolco Pty Ltd ($48,811)
- Summary
- Equipment failures in the mining industry can cause serious safety hazards and substantial financial losses. An automated, cost-effective monitoring system that could be retrofitted to existing equipment would provide advance warning to operators and reduce the likelihood of unscheduled outages. This project will test and validate a vibration-based monitoring system for conveyor belts and associated equipment. It will also identify improved methods to analyse the vibration data to increase the sensitivity and/or accuracy of the alerts that are generated.
- Investigators
- Bronson Philippa, Bruce Belson, Lei Lei and Wei Xiang (College of Science & Engineering)
- Keywords
- Vibration Analysis; Signal Processing; Mining
Department of Industry - Innovations Connections
Internet of Things and Big Data Analytics for Cairns Marine
- Indicative Funding
- $50,000 over 1 year (administered by Cairns Marine), in partnership with Cairns Marine Pty Ltd ($53,109)
- Summary
- This project will assist to analyse the large repository of data held by Cairns marine in relation to its full operations, i.e., from harvest to husbandry, inventory tracking and sales fulfilment. The physical systems currently in use at Cairns Marine are extensive and complex, involving a range of activities in Northern Australia, all activities on site (including R&D) in Cairns and full product (marine animals) stewardship to destination. A deep and informed understanding of data is required by the business to meet its growing global product commitments.
- Investigators
- Wei Xiang, Tao Huang, Lei Lei and Mostafa Rahimi Azghadi (College of Science & Engineering)
- Keywords
- Internet Of Things; big data analytics; marine data; Machine Learning
Verily Life Sciences - Contract Research
JCU Mosquito Trap Development
- Indicative Funding
- $544,184 over 2 years
- Summary
- To design and validate traps that are low cost and sensitive enough for Aedes aegypti and Aedes albopictus mosquitoes that they can be deployed for both SIT release surveillance during suppression and elimination operations, and also for sentinel surveillance after elimination.
- Investigators
- Kyran Staunton, Tom Burkot and Wei Xiang (College of Public Health, Medical & Vet Sciences, Australian Institute of Tropical Health & Medicine and College of Science & Engineering)
- Keywords
- Dengue; Mosquito; trap; Aedes aegypti mosquitoes
Department of the Environment and Energy - National Environmental Science Program (NESP) - Tropical Water Quality Hub (TWQ Hub)
Improving water quality for the Great Barrier Reef and wetlands by better managing irrigation in the sugarcane farming system
- Indicative Funding
- $458,103 over 3 years
- Summary
- This project will work in partnership with industry, extension, NRM, research and government organisations to develop and deploy an irrigation system that is automatically controlled by remotely accessing feedback from the IrrigWeb decision support tool. Irrigweb provides optimal irrigation schedules on a paddock-by-paddock basis by linking information abut climate, soils and management regimes. If new water quality targets as specified in the revised Burdekin Water Quality Improvement Plan are to by met by 2025, it will be critical to establish pathways that enable industry partners to capitalise on new technologies.
- Investigators
- Yvette Everingham, Wei Xiang and Bronson Philippa in collaboration with Stephen Attard (College of Science & Engineering and AgriTech Solutions)
- Keywords
- Irrigation; Water Quality; Great Barrier Reef
Janco Enterprise Pty Ltd - Contract Research
Janco Enterprise Pty Ltd
- Indicative Funding
- $10,000
- Summary
- Machine learning sensor network to maintain optimum conditions and collect data for Molten Oxygen Electrolysis (MOE) reactions. Sensor data collection ? Supervisory capacity Machine learning logic for maintaining optimum reaction conditions on a provided hardware network Supervisory capacity Suggestion of industry standards for data collection and fail-safe implementation Suggestion of hardware components and configuration JCU?s scope in this project: Supervise on sensor quality before purchase and calibration logic once installed into PCB Supervise on any errors in the output value and possible causes Supervise on provided network structures for reliably and continuously recording data from multiple sensors to multiple SBC?s to an academic standard Supervise on methods for machine learning collection of data Supervise on methods provided for protecting sensor hardware in extreme conditions Check failsafe methods and data collection failsafes for industry standards requirements Consult on final hardware design for industrial conditional requirements (Industrial standards reports will be gathered prior to consultation, this is a 2nd check precaution) All mathematical modelling, programming, purchasing of hardware and construction shall be completed by JE Pty Ltd
- Investigators
- Wei Xiang in collaboration with Kang Han (College of Science & Engineering)
- Keywords
- Internet Of Things; Sensory data processing; Machine Learning
Department of Industry - Smart Cities and Suburbs Program
Council improving the water quality of the Great Barrier Reef through the use of smart sensors and the IoT for urban water management
- Indicative Funding
- $360,146 over 1 year (administered by Cairns Regional Council)
- Summary
- The primary aim of this grant application is to bring smart city technology into urban water management to improve urban water quality discharging to the Great Barrier Reef by: 1). Developing IOT technology to manage large data sets obtained from existing smart meters and water quality monitoring probes to make effective management decisions; and 2) Supporting the development of new cost effective, real time water quality monitoring technology. This grant application is for purchase of commercially available water quality monitoring probes suitable for a tropical urban stormwater environment, for supporting the development of new real time monitoring technology for nutrients; for the development of data analysis tools using IOT technology for both smart meter water consumption data, sewer pump station overflow data and stormwater water quality data so that the data is available in real time and can be used for effective decision making.
- Investigators
- Wei Xiang, HanShe Lim and Niels Munksgaard in collaboration with Lynne Powell (College of Science & Engineering and Cairns City Council)
- Keywords
- IoT infrastructure; Smart water sensors; Real-time water quality monitoring; Great Barrier Reef water quality; Urban water management
- Supervision
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Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.
These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.
- Current
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- Development of high-level programming tools to improve the robustness of Internet of Things networks. (PhD , Secondary Advisor/AM)
- Massive Multiple-input and Multiple-output (MIMO) Technique for Visible Light Communications (VLC) Systems (PhD , Primary Advisor/AM/Adv)
- Explainable AI for Medical Imaging (PhD , Primary Advisor/AM/Adv)
- Defending against Cyber-attacks targeting AI-enabled Applications in Industry 4.0 (PhD , Secondary Advisor)
- Completed
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- Development of machine learning schemes for use in non-invasive and continuous patient health monitoring (2021, PhD , Primary Advisor/AM/Adv)
- Deep learning for internet of underwater things and ocean data analytics (2022, PhD , Secondary Advisor/AM)
- Light field reconstruction from multi-view images (2023, PhD , Primary Advisor/AM/Adv)
- Decision Support System for Precision Agriculture using Deep Learning (2023, PhD , Secondary Advisor/AM)
- High efficient tag identification protocols for large-scale RFID systems (2018, PhD , Primary Advisor)
- Simulation and implementation of novel deep learning hardware architectures for resource constrained devices (2023, PhD , Secondary Advisor/AM)
- Collaboration
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The map shows research collaborations by institution from the past 7 years.
Note: Map points are indicative of the countries or states that institutions are associated with.- 5+ collaborations
- 4 collaborations
- 3 collaborations
- 2 collaborations
- 1 collaboration
- Indicates the Tropics (Torrid Zone)
Connect with me
- Phone
- Location
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- A2.122, A2 (Cairns campus)
- Advisory Accreditation
- Advisor Mentor
- Find me on…
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My research areas
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