Electrical and computer engineering

Supervisor: A/Prof Weidong Xiao

Eligibility: Strong in power electronics and control engineering; Hands-on experience for prototyping is a plus.

Project Description: Collaborated with a UK high-tech company, the project aims to develop a prototype of a high-efficiency converter using wide-band-gap power semiconductors. One or two students are required to work with one industry engineer for the development. The student(s) gain real-world industry experience, which is good for the future career. 

Requirement to be on campus: Yes *dependent on government’s health advice.

Supervisors: Dr. Wibowo Hardjawana

Eligibility: Strong background in wireless communication and deep learning, equivalent to the one covered in ELEC5508 Wireless Engineering

Project Description: Each generation of cellular communication systems is marked by a defining disruptive technology of its time, such as orthogonal frequency division multiplexing (OFDM) for 4G or Massive multiple-input multiple-output (MIMO) for 5G. Since artificial intelligence (AI) is the defining technology of our time, it is natural to ask what role it could play for 6G. The project aims to demonstrate a 6G vision of a new air interface and end-to-end learning PHY, which AI partially designs to enable optimised end-to-end communication schemes for any hardware, radio environment, and application. The specific tasks of the project are to modify and/or add existing wireless communication reference design to facilitate end-to-end learning by including AI in the wireless air interface. Students will need to compare its performance with a standard communication system.

Requirement to be on campus: No

Supervisors: A/Prof. Zihuai Lin, Prof. Branka Vucetic,

Eligibility: up to 2 students are required for this project. The students participating in this project should have good knowledge of radio frequency engineering. Programming skills are essential. The students with average marks above 75 are preferred.

Project Description: In this project, we aim to develop a low cost X-ray vision wireless hand-held device. The developed hand-held device can be used to see through walls to track moving human bodies. The technique would be based on a concept similar to radar and sonar imaging, instead of using high power signal, this one would use low power Wi-Fi or mmWave/THz, UWB signals to track the movement of people behind walls and closed doors.  When an RF signal is transmitted towards a wall, due to the absorbing property of the walls, only a small part of the signal can be penetrated through the wall and can be reflected back when the signal reaches any objects that happen to be moving around in the other room. Based on the reflected signal, we can detect the moving objects. 

Requirement to be on campus: Yes *dependent on government’s health advice.

Supervisors: A/Prof. Zihuai Lin, Dr. Audrey Wang, Prof. Branka Vucetic

Eligibility: up to 2 students are required for this project. The students participating in this project should have good knowledge on hardware development. Programming skills are essential. The students with average marks above 75 are preferred.

Project Description: This project will develop novel solutions for IoT based pressure injury monitoring to enable smart hospitals, smart healthcare and provide in-patients with good treatment experience.

IoT is a key enabler for our future smart hospital and healthcare to effectively overcome the major problems, such as nursing staff shortness, impractical physical care environments and difficulties in identifying patents’ needs, etc.  In order to enable a fast uptake of the IoT pressure injury monitoring systems, key issues, such as data collection and sensing, pressure injury prediction modelling,  and hospital validation, should be addressed. These problems are the major technological obstacles which are preventing industrial partners from further expanding their business in the hospital IoT area.

We will develop a smart mat for pressure injury monitoring. The proposed smart mat consisting of a pressure sensor array and a moisture sensor array will be tested and validated in the Westmead hospital. The collected data will be transmitted to the cloud via WiFi or other wireless networks for data processing and analysis. The developed deep learning algorithms for smart mat will be used to obtain the weight and moisture distribution of the inpatient’s body as well as the respiratory rate.

Requirement to be on campus: Yes *dependent on government’s health advice..

Supervisors: Dr. Zihuai Lin, Dr. Audrey P Wang, Dr. Callum Parker

Eligibility: up to 2 students are required for this project. The students participating in this project should have good knowledge on smart phone APP development. Programming skills are essential. The students with average marks above 75 are preferred.

Project Description: This project is to develop an Internet of Things network and platform architecture suitable for the Westmead Precinct consisting of location sensors, people counting sensors and an interactive way-finding app e.g.an augmented reality (AR) mobile app. The design of the proposed platform and data processing architecture will aim to future-proof IoT network capabilities to allow more connected devices including environmental sensors to be incorporated such as temperature, humidity, and air quality.

The project is based on a multi-sensor data fusion artificial intelligence algorithm, which can geolocate compatible smartphones inside buildings. This algorithm achieves higher accuracy by leveraging pre-existing information of the environment (Bluetooth, WiFi…) combined with sensors that allow inferring the movement of the user (compass, gyroscope, accelerometer, barometer…).

The information can be fed into the indoor wayfinding and navigation solution to guide hospital visitors to always find the most suitable route to their destination, based on their stated preference.

Requirement to be on campus: Yes *dependent on government’s health advice.

Supervisor: Prof Abbas Jamalipour

Eligibility: Necessary: Evidence of knowledge in telecommunications systems, good programming skills (C++, MATLAB, Phyton); Desirable: Knowledge in communications network security

Project Description: Cell-free wireless communications is a new paradigm within the future 6G networks towards implementation of the Internet of intelligence with connected people and things. In a cell-free network, many distributed access points are connected to a central processing unit and serve a smaller number of users over the same time-frequency resources.

The system has shown great potential in improving network performance in some perspectives compared to the co-located and conventional small-cell systems. The next-generation Internet-of-Things systems could be dispersed over large areas under a cell-free network setting. This has given rise to security concerns stemming from the exposure of wireless channels and the exponential growth of connected devices.

In this project you will develop new techniques for cover communications in cell-free networks and evaluate performance of those techniques against existing technologies.

Requirement to be on campus: The project requires regular meetings with the supervisor. It can be done remotely or in-person. While the project can be done remotely, in-person discussions and meetings might be required on multiple occasions.

Supervisor: Dr. Sinan Li

Eligibility: High Distinction in Control courses (for example, ELEC3304 or similar); Experience in digital systems design, embedded systems. For undergraduates, must have already completed at least 96 credit points towards their undergraduate degree at the time of application.

Project Description: Control systems are an integral part of everyday life. From solar power generators to industrial robotics to flying drones to autonomous-driving cars, control systems are there to ensure the performance, safety and reliability of these systems. However, these systems are often subject to uncertainties, nonlinearities and communication delays, making the design of optimal control systems challenging.

We have developed a model-free control theory that does not require precise knowledge of system models to achieve the objectives. Without the need for precise system models, the control method can naturally bypass most of the above challenges and achieve better performance than conventional model-based methods, such as linear control, model-predictive control, sliding model control, etc.

This project will further investigate model-free control, improve our existing methods and characterise the performance advantage over conventional techniques. It will be carried out in collaboration with Ms Wanrong Li and Mr Yuhan Zhang (both are PhD students in the Future Energy Network Lab).

Requirement to be on campus: Yes *as per government’s health advice.

Supervisors: Prof Xiaoke Yi, Associate Prof Luping Zhou, Dr Liwei Li

Eligibility: Year 3/4/5 or Master students; Electrical engineering, Mechatronics, Computer engineering, Software engineering or Computer science

Project Description:

The state-of-the-art sensing technology is rapidly growing and will play a critical role in the near future. For instance, smart phones, which play a significant role in our daily life, have a fingerprint identity sensor that makes it easy for us to access the device, and they also use an ambient brightness sensor to adjust the display brightness, etc.

The project is to deliver the superior, advanced sensing platforms assisted by machine/deep learning to address the important challenges across a diverse range of applications in various fields, particularly in lab-on-chips, Internet of Things, broadband communications and biomedical applications. The internship project focuses on electrical circuits design and data processing as well as machine learning and software programming. The aim is to realize ultra-sensitive, high resolution and extreme-range sensing.

The intern will closely work with a research team including PhD students and postdoctoral research associates. Innovative signal processing and design in both hardware and software will be carried out during the project.

Requirement to be on campus: Yes *as per government’s health advice.

Supervisors: Prof Xiaoke Yi, Dr Liwei Li

Eligibility: Year 3/4/5 or Master students, Electrical engineering,  Mechatronics, Computer engineering, Software engineering or Computer science

Project Description:

Electro-optic modulators encode electrical signals onto an optical carrier. They are essential for the operation of global communication systems and data centers for artificial intelligence, broadband networks, and high-performance computing.

The project focuses on the development of an ultra-wideband electro-optic modulator. Addressing the challenges associated with achieving a large modulation bandwidth entails reducing microwave attenuation and realizing velocity and impedance matching. It is also essential to optimize the modulation electrode and optical waveguide jointly. The project will advance signal modulation techniques, paving the way for enhanced optical communication and modulation capabilities.

Requirement to be on campus: Yes *as per government’s health advice.