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Postgraduate Electrical and Computer Engineering

17 November 2023

Why choose postgraduate study?

The department has postgraduate students spanning several research disciplines including power systems, materials and nanotechnology, communications, acoustics, computational imaging, neural engineering, power electronics and radio frequency engineering.

Our research and teaching activities are supported by excellent laboratory facilities and technical staff. Several of the facilities are not available at any other university in New Zealand.

These include some of the nanofabrication facilities and analysis instruments which are part of the MacDiarmid Institute, the High Voltage Laboratory and the Electrical Machines Laboratory. We have strong ties with the EPECentre for power systems engineering.

Getting started

The first step to becoming a postgraduate student is finding a supervisor and research area. See our full list of academic staff and our areas of research. Funding advice is available from the College of Engineering's scholarships page.

Department seminars

All postgraduate students are expected to attend our regular departmental seminars.

Postgraduate research projects

Associate Professor Paul Gaynor


I currently have a few main areas of research interest that have projects available: Biomedical electronics, electric power generation and converter technology, and small-scale electric vehicles.

Note: If you have any of your own research project ideas in the general areas of biological electric field applications, electric power generation and converters, or power electronics applications (including electric vehicles), then let me know and we'll talk about the possibilities. 


Biomedical Electronics

Electrical Cell Movement and Alignment using Micro/Nano–scopic Electrode Systems (ME or PhD Project) Assoc Prof Paul Gaynor

Nonlinear AC electric fields can be used to physically move cells. This effect is to be optimized for the purposes of cell movement in modern biomedical applications. The project requires a student with an interest in biological systems and is confident with manual skills. The project will be carried out in collaboration with scientists from AgResearch.


Bio-feedback Swallowing Rehabilitation (ME or PhD Project) Assoc Prof Paul Gaynor

This project involves the design, building and testing of both electronics hardware and software to carry out biofeedback-based swallowing rehabilitation. Specifically, the system needs to be developed such that a smartphone app can be used to wirelessly link to the electronics involved with swallowing sensing and display biofeedback information in real time. This project is being carried out in collaboration with the Communication Disorders Department and the New Zealand Brain Research Institute.


High Voltage Liquid Disinfection System (ME Project) Assoc Prof Paul Gaynor

Further development of a high-voltage method for liquid disinfection is required. This is a highly practical and hands-on project where stuff actually gets built and tested. The development is mainly around design that reduces power consumption and increases kill-rates. The project requires a practically-minded student with a desire to play around with some power.  


Integrated Electrically-Mediated Cancer Therapy System (ME or PhD Project) Assoc Prof Paul Gaynor

Research is being carried out on the creation of high voltage apparatus for combined electric field pulsing and heating for a new multi-modal cancer therapy process. This apparatus will need to be integrated into a system that is appropriate for application to clinical trials. This project is being carried out in collaboration with researchers from both Christchurch and Dunedin Hospitals. 


Electric Vehicles

Modular Multilevel Inverter for Electric Vehicle Applications (ME or PhD Project) Assoc Prof Paul Gaynor

This project involves the design and build of a motor controller/inverter that eliminates some significant compatibility problems and improves energy efficiency. Once electric vehicles become more common, the electrical noise they create will become more of an issue, forcing new low-noise solutions to be implemented.  Modular multilevel inveters are one possible solution.  This project requires a student with an interest in power electronics and programming (this sort of inverter can only be implemented with digital control).


Modular Swappable Compact Electric Vehicle Systems (ME Project) Assoc Prof Paul Gaynor

This project involves the design and build of a set of small electric vehicle modules that can be easily swapped between different electric vehicle platforms. The concept is much like that of battery power tools that allow you to use the same battery in multiple tools.  In this case though, these modules include not only the battery, but also motors, controllers, and inverters.  This means you can swap the main electric power parts of say an urban electric car with an electric motorcycle, or perhaps an electric watercraft, depending on what vehicle you want to use at any given time. Such a modular system saves valuable and expensive resources and is a considerably more sustainable way to approach personal powered transportation.


Stirling Engine Power Generation

Low Temperature Differential Electrically-Controlled Stirling Engine (ME or PhD Project) Assoc Prof Paul Gaynor

This project is highly practical and quite mechanical, requiring the design, construction and control of a low temperature differential Stirling engine to efficiently output around 1kW of electrical power. A great deal of the mechanical superstructure has been built in a previous Masters project, but there is scope for some redesign and fabrication. A significant amount of electronics is involved with the sensing of pressure, temperature, and position, and the control of the engine and load characteristics.


Power Converters for Isolated Dwellings (ME Project) Assoc Prof Paul Gaynor

There is a humanitarian need to design low-cost power converters that can be used by those in remote areas with small amounts of power generation capacity (nominally 500 W – 1 kW), who wish to connect to their own household to an electrical power supply. This is a highly hands-on power electronics project that will result in a skill base and knowledge many employers will find very attractive. 


Professor Neville Watson


Power Quality in Electrical Networks & Computer Analysis of Electrical Power Systems

Power Quality has been a major area of research for our group here over many years. There are two sides to this, the first is the performance of the electrical devices (both generation and loads) the second is the performance and characteristics of the electrical network itself and what it can withstand. The steps to be taken on both sides involve characterization, development of suitable models and the investigation of possible mitigation methods for the power quality issues.

Watson N.R. and Arrillaga J., “Power Systems ElectroMagnetic Transients Simulation”, IEE Books 2003.

Arrillaga J. and Watson N.R. “Power System Harmonics”, 2nd Edition, John Wiley & Sons 2003.

Arrillaga J., Smith B.C., Watson N.R. and Wood A.R., “Power System Harmonic Analysis”, John Wiley & Sons 1997.

Arrillaga J., Chen S. and Watson N.R., “Power System Quality Assessment”, John Wiley & Sons 2000.

Watson N.R., Power-Quality Management in New Zealand, IEEE Trans. on Power Delivery, Vol. 31, No. 5, Pages: 1963 - 1970, 2016


Estimation Techniques (ME/PhD Project) Prof Neville Watson

Power Quality State Estimation

Due to the cost of PQ monitors it is not economic to monitor the complete system and estimation techniques can give useful information at unmonitored locations. Although good progress has been made there is a need to continue the development.

Watson, N.R.; Farzanehrafat, A., "Three-phase transient state estimation algorithm for distribution systems," IET Generation, Transmission & Distribution,  vol.8, no.10, pp.1656-1666, October 2014


Use of Smart-meter data

This project will look at the potential benefits smart-meter data will bring to the operation of an electrical power network.

Watson J.D.,  Welch J. & Watson N.R., Use of Smart-meter data to determine Distribution system topology, IET The Journal of Engineering, March 2016, 8 pp.


Simulation Techniques (ME/PhD Project) Prof Neville Watson

Harmonic Domain Modelling of Distribution Systems

The Harmonic Domain has been developed for accurate modelling the interaction of non-linear loads, such as HVDC links and FACTS devices in transmission systems. With the large scale deployment of power electronic consumer equipment as well as the use of embedded generation with inverter interfaces, the need to accurately model their interaction is important and the direct harmonic current injection technique is not adequate for this situation. This project aims at developing new models in the Harmonic Domain and benchmarking the use of Harmonic domain against direct harmonic current injection technique for distribution system modelling.


Harmonic State-Space

Harmonic State-Space (HSS) is an extension of the Harmonic Domain. It is complex but has great potential and in need of developing further.

J.B. Kwon, Wang X., F. Blaabjerg, C.L. Bak,A.R. Wood & N.R. Watson, Linearized Modeling Methods of AC-DC Converters For an Accurate Frequency Response, Journal of Emerging and Selected Topics in Power Electronics, vol. PP, no.99, pp.1-1

J.B. Kwon, Wang X., F. Blaabjerg, A.R. Wood & N.R. Watson, Harmonic Instability Analysis of a  Single-phase Grid-connected Converter using a Harmonic State-Space Modeling Method, IEEE Trans. of Industrial Applications, Vol. 52, No. 5, Sept/Oct. 2016, pp.4188-4200


Electromagnetic Transients Simulation

Electromagnetic Transient Simulation is an important aspect of any engineering design, however, the results are only as good as the component models and algorithm used. This project is aimed at furthering the state of the art in simulation techniques and system representation. One possible extension is the use of root-matching method inside component model such as the UMEC transformer model.


Impact Studies and mitigation (ME/PhD Project) Prof Neville Watson

Worldwide attention is on Smart Grids and the benefits and issues this will bring. This project is aimed to contribute to the body of knowledge by looking and the impact of new technologies of the system and was to mitigate it. The integration of renewable energy sources such as wind and PV, the uptake of electric vehicles, the used of power-electronic equipment evaluated (HVDC, SVC, STATCOM, DVR, Voltage regulators,…) needs to be studied and the mitigation methods carefully considered. Control of equipment in important to ensure unwanted interactions do not occur.

J.D. Watson, N.R. Watson, Bhaba Das, “Effectiveness of Power Electronic Voltage Regulators in the Distribution Network”, IET Generation, Transmission & Distribution, 2016, Vol. 10, No. 15, Pages: 3816 - 3823, (Published,

J.D. Watson, N.R. Watson et al, Impact of Solar Photovoltaics on the Low Voltage Distribution Network in New Zealand, IET Generation, Transmission & Distribution 2016, Vol. 10, No. 1, pp. 1–9

Artificial Intelligence in Power Systems (ME Project) Prof Neville Watson

Artificial Intelligence techniques are now filling the power system journals as people research ways of gainfully using these techniques in power systems. Power system optimisation and control are areas that have potential due to the complexity of modern power systems. Processing the vast amount of power system information is another task AI techniques are being used for. This project is to investigate then implement an AI technique to optimise the power system. The optimisation of the power system is very important due to the significant benefits that can be achieved. Conventional optimisation techniques have difficulties due to the many constraints and multiple minima points and discrete nature of some parameters (Tap-position of transformers). Another interesting area is the use of AI techniques to optimise the design of harmonic filters for a given application.


Resilience of the Electrical Network (ME Project) Prof Neville Watson

As has been demonstrated with the earthquakes in Christchurch and Kaikoura electricity is an important lifeline. Not only do storms, earthquakes, hurricanes impact the ability to supply electricity but the telecommunication infrastructure is intertwined and inter-dependent. It is important to understand the interdependency and susceptibility to storms and earthquakes to determine the resilience of the electrical network.

Balasubramaniam K., Venayagamoorthy G.K. and Watson N.R.,, Situational Awareness System for Power Grids, Power Systems Conference 2013, March 12-15, 2013, Madren Conference Center, Clemson University, Clemson, SC

Balasubramaniam K., Venayagamoorthy G.K. and Watson N.R., “CNN based Power System Transient Stability Margin and Voltage Stability Index Predictions”, IEEE Symposium Series on Computational Intelligence 2013, Paper ID: 991, 15 - 19 April 2013, Singapore

Balasubramaniam K., Venayagamoorthy G.K. and Watson N.R.,, "Cellular neural network based situational awareness system for power grids," Neural Networks (IJCNN), The 2013 International Joint Conference on, Dallas, TX, USA,  2013, pp. 1-8.


Other academics working in this area:

Dr Alan Wood

Dr Andrew Lapthorn


Professor Phil Bones 


Imaging near metal with MRI (PhD Projects) – Prof Phil Bones

A current doctoral student has developed an algorithm for performing fat suppression near implants in patients.  This has the potential of allowing better and safer diagnosis of post-implant complications than is currently available via X-ray imaging.  To date promising results have been obtained with 2D images of phantoms and a small pilot clinical study is planned. Part of the work was completed at the Lucas Imaging Center, Stanford University.  We plan to extend this work to three-dimensional imaging and to find better methods of incorporating prior knowledge (e.g., of the type of implant) into the imaging process.  There is scope for several doctoral projects and more collaboration with Stanford University.


Markerless Motion Tracking for Motion Correction in MRI (PhD project) – Prof Phil Bones

We are developing methods for detecting and correcting motion effects in magnetic resonance imaging (MRI). We have already developed, tested and published new algorithms for successful detection and correction of motion disturbances with postprocessing (i.e., performing the correction after the scan is finished). This approach is limited to certain types of motion. We now seek to measure the motion of the region being imaged in real-time and alter the scan parameters dynamically to achieve an artifact-free image. This challenging project involves advanced algorithms and instrumentation. It would suit someone with an interest in signal processing and/or medical imaging. Supervisors: Philip Bones, Julian Maclaren (University of Stanford, California).


Signal Delay in Cascaded Multirate DSP Systems (ME/PhD Project) – Prof Phil Bones

Multirate methods offer excellent efficiency for many signal processing tasks implemented on DSP devices. While a lot has been written about the efficiency, less is known about the signal delay properties of multirate designs. Preliminary work by Phil Bones seems to indicate that signal delay can be quite severe in some situations. The project will study in detail a number of common multirate configurations and design a software tool which can be used to estimate performance, both in terms of computation and signal delay. At least one publication in a quality journal can be expected.


Master of Engineering in the Department of Electrical & Computer Engineering (ECE) – Prof Phil Bones
A student is sought to contribute instrumentation and experimental methods for a project research into the properties of films of nanoparticles (percolating films).  A group headed by Professor Simon Brown is experimenting with the films which exhibit interesting properties when varying voltages are applied*.  In particular, there is the possibility that the percolating films might be used for learning and pattern recognition in a manner similar to certain types of neural networks.  A YouTube presentation about the project is available.
The project can involve several of the following aspects, depending on the strengths and interests of the student:

  1. Methods and instrumentation for resolving high speed switching events in current waveforms while time-varying voltage waveforms are applied;
  2. Programmable switching and detection networks for interconnecting and driving experimental arrays of electrodes;
  3. Experiments with lithographically formed electrodes and gates for controlling percolating panels;
  4. Programmable sequence generation and output logging for experimental arrays of electrodes connected to a percolating panel;
  5. Implementing an output layer neural network in CMOS for connection to electrodes connected to a percolating panel.

The ME student would be supervised by Professor Phil Bones, in association with Dr Steve Weddell (ECE) and Professor Simon Brown (Physics & Astronomy).

* S. Fostner and S. Brown, “Neuromorphic behavior in percolating nanoparticle films”, Phys. Rev. E, American Physical Society, vol. 92, no. 5, 2015. 


Dr Richard Clare


Images of astronomical objects with ground-based telescopes are blurred by atmospheric refractive index variations that evolve with time. Adaptive optics is an opto-mechatronic system that can overcome the effects of the earth’s atmosphere and reduce the amount of blurring. Adaptive optics systems consist of a sensor, which measures the instantaneous wavefront distortion due to the atmosphere, an adaptive mirror that can be locally deformed by independent actuators, and a control law to calculate the optimal actuator commands from the wavefront sensor measurements and atmospheric and noise statistics.

Currently the next generation of Extremely Large Telescopes are being designed and built, including the European Southern Observatory’s (ESO) European Extremely Large Telescope (EELT) (below), a 39m diameter primary mirror telescope, which will be the world’s largest optical telescope when finished. The following projects are offered in collaboration with ESO on the design of the adaptive optics systems for the EELT, including solving various signal and image processing, and control problems. In particular, I am a partner in the software project OCTOPUS, which is a parallelized C (MPI) tool to numerically simulate the atmosphere, telescope and adaptive optics systems in order to design the wavefront sensor and reconstruction algorithms.


Pyramid Wavefront Sensing with Laser Guide Stars (PhD Project) Dr Richard Clare

The pyramid wavefront sensor operates by focusing the incoming light beam on the apex of a four sided pyramid and producing four images. The local relative brightness of these four images gives the slope of the wavefront locally in the aperture. Pyramid sensors are popular for natural guide star based sensors but so far have not been implemented with artificial laser guide stars. This project will involve analysing pyramid type sensors with a sodium laser guide star (at a finite height of 90km vs a natural guide star at infinity), simulating the pyramid sensor and laser guide star in the Octopus simulation tool, and developing algorithms to reconstruct the wavefront efficiently. There is also the potential to use the adaptive optics test bench in the optics lab to test the proposed algorithms.


Non-modulated Pyramid Wavefront Sensing (PhD Project) Dr Richard Clare

The pyramid wavefront sensor is popular in adaptive optics because of its increased sensitivity in closed loop. However, it requires a mechanical modulation of the light with a tip-tilt mirror to increase its linear range. This project involves looking at introducing static phase screens to increase the linear range without requiring the mechanical modulation. This project will involve analysing different types of phase screens with pyramid type sensors (including different number of sided prisms), numerically simulating their performance in the OCTOPUS simulation package, and verifying their performance on the adaptive optics bench in the optics laboratory.


Shack-Hartmann Wavefront Sensing with Laser Guide Stars (ME Project) Dr Richard Clare

The most commonly used wavefront sensor in adaptive optics is the Shack-Hartmann sensor, which consists of an array of lenses (subapertures) that can determine the local slope of the wavefront in each subaperture by finding the centroid (centre of mass) of each subaperture image. A number of algorithms have been proposed to perform this centroiding. This project involves numerically evaluating these algorithms (and improving them where possible) for different atmospheric and environmental conditions in the Octopus simulation package.


Selected Publications

R. Muradore, L. Pettai, R. Clare, and E. Fedrigo, "An application of adaptive techniques to vibration rejection in adaptive optics systems," Control Engineering Practice. 32, 87-95 (2014).

R. M. Clare, M. Le Louarn, and C. Béchet, "Laser guide star wavefront sensing for ground-layer adaptive optics on extremely large telescopes," Applied Optics 50, 473-483 (2011).

R. M. Clare, M. Le Louarn, and C. Béchet, "Optimal noise-weighted reconstruction with elongated Shack–Hartmann wavefront sensor images for laser tomography adaptive optics," Applied Optics 49, G27-G36 (2010).


Adjunct Prof Richard Jones


Richard is Director of the Christchurch Neurotechnology Research Programme ( based at New Zealand Brain Research Institute ( and a joint venture between University of Canterbury (Electrical and Computer Engineering, Psychology, Law), University of Otago, Christchurch (Medicine), and Canterbury District Health Board (Medical Physics and Bioengineering, Sleep Unit).  Richard also leads the closely related Neural Engineering Research Group in ECE (

Several PhD projects are on offer within our Lapse Research Programme. These will be of particular interest to students with strong interests and expertise in signal and/or image processing and keen to apply and improve their skills in a fascinating, albeit challenging, area of biomedical/neural engineering.


Projects on offer are: 

  1. Identification, enhancement, and localization of deep neuroelectric features during and preceding microsleeps in the brain in real-time  
  2. Fusion of fMRI and EEG to achieve optimal information on spatiotemporal dynamics of lapses (including different types) in the brain  
  3. Reservoir computing approaches to EEG-based prediction of microsleeps
  4. Automated behavioural detection and classification of lapses of responsiveness in the laboratory                    
  5. Neural activity (fMRI and EEG) during the recovery phase of behavioural microsleeps                      
  6. Physiological biomarkers and mechanisms in the brain of lost-attention lapses     
  7. Physiological biomarkers and mechanisms in the brain of mind-wandering 
  8. Detection of exogenous diverted-attention lapses      
  9. Real-time estimation of cognitive load and mental state (levels of stress, anxiety, boredom, alertness) from EEG    
  10. Microsleeps in the real world: Air-traffic controllers
  11. Detection of lost-attention lapses from EEG 
  12. Depth neuroelectric recordings in the brain towards mechanisms of causation of and recovery from microsleeps     
  13. Vigilance versus Mindlessness versus Mind-wandering versus diverted attention
  14. Lapses in responsiveness – The influence and underlying mechanisms of consequences      
  15. Microsleeps versus lost-attention lapses: Behavioural and physiological differences with time-on-task, task complexity,  and sleep restriction
  16. Resource depletion with time-on-task  
  17. Microsleeps in the real world: Driving  
  18. Can ocular features (eye blink, closure, gaze) and/or ECG features (heart rate variability) helpful in prediction of microsleeps over EEG features alone?            
  19. Could lost-attention lapses be due to instances of local sleep in the brain?


Other academics working in this area:

Associate Professor Michael Hayes

Professor Rick Millane

Dr Steve Weddell

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