Congratulations to the recipients of CIN’s 2023 PhD scholarships.
Winners have been awarded to representatives from CIN member universities as follows:
The University of New South Wales
— Jinhong Yuan
This project will develop novel delay-Doppler multi-carrier transmission and receiving techniques for low-earth-orbit satellite-based non-terrestrial wireless networks (LEO-NTN). The outcomes from this project are expected to contribute to supplying state-of-the-art connectivity techniques of LEO satellite communications and contribute to connecting Australia’s rural/regional areas and communities.
— Salil Kanhere
The University of Sydney
— Yonghui Li
The project aims to develop a wide-area massive multi-access framework, which can provide cost-effective and spectrally efficient broadband services, accommodating a massive number of users and devices over large geographical areas. This can lead to a significant reduction in the number of base stations required to provide broadband services to a massive number of users in rural and remote areas, resulting in lower deployment costs. This can help reduce the overall cost of broadband services, making them more affordable and accessible to people in rural and remote areas.
— Suranga Seneviratne
University of Newcastle
— Duy Ngo
This project aims to enhance Australia’s capability for bushfire prediction in large areas without needing to deploy extensive sensors, by enabling recently launched LEO satellite constellations to perform remote imaging and in-satellite training of prediction models. Expected outcomes include new transmission designs and resource management schemes that enable distributed machine learning over satellite links with intermittent connectivity and limited resources.
— Scott Brown
Cybersecurity is crucial in our increasingly connected world, but it remains a challenge due to the rising number of attacks. While software tools have advanced, human operators remain vulnerable. To address this, we suggest using scientific methods to enhance the interaction between human operators and cybersecurity tools, ultimately strengthening overall security.
Charles Sturt University
— Lihong Zheng
Multi-Source Data Fusion and Deep Learning for 3D Flood Mapping
This project aims to improve 3D flood mapping accuracy by fusing data from multiple sensors using deep learning algorithms. It will estimate water surface and inundation depth for more effective emergency response. This project has the potential to significantly enhance flood mapping accuracy, thus mitigating the impact of flooding events.
— Rafiqul Islam
University of Wollongong
— Qinghua Guo
— Ashish Agalgaonkar
The University of Technology, Sydney
— Jahangir Hossain
Data driven design and management of shared energy resources to improve power supply resilience in communication networks
This project aims to develop a data driven approach for sharing and managing energy resources in power communication network base stations to achieve higher resilience through better visibility, coordination, and management of shared energy resources in optimal ways. The intended outcome of the project is a framework to design, prioritise, share, and optimise energy scheduling with quantified resilience. End-users will benefit from improved reliability and avoid system failures triggered by extreme weather events.
— Peiyuan Qin
This project aims to develop unmanned aerial vehicle (UAV) aided low earth orbit (LEO) communications by employing novel low-energy-consumption steerable antennas. UAV aided LEO communications can provide high-speed internet for poorly connected or unconnected communities in rural and remote areas. This project will generate significant scientific breakthroughs in many aspects of antenna research.
Southern Cross University
— Golam Sorwar