Doctoral study in Computer Systems Engineering
Why study with us?
- Enrolment at the highest-ranked Engineering faculty in New Zealand and 107th in the world (QS World University Rankings by Subject, 2025)
- Opportunities to be supervised by experts in the field, such as pioneers in Wireless Power Transfer and world-class collaborators at the Centre for Automation and Robotic Engineering Sciences
- Connections to professional, industry and research organisations, such as the Institute of Electrical and Electronics Engineers and the Association of Computing Machinery
- Access to Postgraduate Research Student Support (PReSS) funding for research expenses
Research opportunities
Pursuing a PhD at our University gives you access to a high-calibre research community – you may have the opportunity to publish papers, attend international conferences and develop your network in academia and industry.
We welcome research proposals in topics relating to our key areas, including:
- Embedded systems, emphasising hardware/software design, real-time systems, low-power design, application-specific processors, system-level languages and compilers, ubiquitous and wearable computing, smart sensors, medical devices, intelligent transportation systems, the Internet of Things, and hardware (FPGA) acceleration of artificial neural networks
- Robotics, focusing on areas such as human-robot interaction, software systems and tools, and applications in essential sectors such as healthcare and agriculture
- Digital health, modelling biological cells, pacemaker testing, and emulating human organs on Field Programmable Gate Arrays
- Ultra high-speed computations, exploring advanced techniques for processing high bandwidth data streams and big data.
- Industrial informatics, combining information processing, control systems, and communication technologies for enhancing efficiency and production of industrial systems.
- Industrial automation control, emphasising novel approaches to software systems used in control based on formal models of computation and used to develop complex centralised and distributed control systems
- Applied deep learning, focusing on impaired speech processing and recognition systems, and intelligent health diagnostic and screening systems
- AI in healthcare, bringing together machine learning, healthcare, and software engineering to create innovative solutions that transform healthcare delivery. See DeepNet Discovery Network
Our people
Associate Professor Catherine Watson
Associate Professor Catherine Watson has been working in the field of speech processing for nearly 30 years. Her research focus is speech production in machines and people, with a particular interest in the acoustic phonetics of New Zealand English (NZE) and Te Reo Māori. She also does research in intonation, creating NZE and Te Reo voices for speech synthesis, voice morphing, emotion, speech for robots and visual feedback for speech pronunciation and voice quality. She is interested in both modelling the vocal tract and the glottal source. She has been awarded three Marsdens: two on sound change in Te Reo, and one on sound change in NZE.
More researchers in Computer Systems Engineering
- Associate Professor Avinash Malik
- Professor Bruce MacDonald
- Associate Professor Kelly Blincoe
- Associate Professor Kevin Wang
- Associate Professor Morteza Biglari-Abhari
- Dr Nasser Giacaman
- Dr Nitish Patel
- Dr Maryam Hemmati
- Professor Oliver Sinnen
- Professor Partha Roop
- Associate Professor Waleed Abdulla
- Dr Reza Shahamiri
- Professor Zoran Salcic
Past research topics
- Improving the security of multiprocessor-based embedded system designs | Supervised by Associate Professor Morteza Biglari-Abhari and Professor Zoran Salcic
- The computers have a thousand eyes: Towards a practical and ethical video analytics system for person tracking | Supervised by Associate Professor Morteza Biglari-Abhari and Associate Professor Kevin Wang
- Contributions towards dynamic intelligent software systems | Supervised by Professor Zoran Salcic and Associate Professor Kevin Wang
- Context-aware activity recognition for elderly healthcare using wearable sensors embedded in the environment | Professor Zoran Salcic and Associate Professor Kevin Wang
- Timing analysis and design optimization for GALS systems on time-predictable multi-core architectures | Supervised by Professor Zoran Salcic, Associate Professor Avinash Malik and Associate Professor Morteza Biglari-Abhari
- Safety analysis of human car following models | Supervised by Professor Partha Roop and Associate Professor Avinash Malik
- Cloud computing with Annotation Parallel Task (@PT) | Supervised by Professor Oliver Sinnen and Dr Nasser Giacaman
- Optimal task scheduling on parallel systems | Supervised by Associate Professor Oliver Sinnen and Professor Matthias Ehrgot
- Performance optimisation of AI and machine learning, including scheduling of inference and training tasks, optimisation of GPU usage, design and implementation of algorithms on Neural Processing Units (NPUs) | Supervised by Professor Oliver Sinnen
- Efficient algorithms for small Satellites, including high-performance embedded computing, energy efficient designs, design of Neural Processing Unit (NPU) implementations, fault tolerance | Supervised by Professor Oliver Sinnen
- Programming behaviour of personal service robots with application to healthcare | Supervised by Professor Bruce MacDonald and Professor Elizabeth Broadbent
- Hand Vein: A Distinctive and Non-Contact Biometric Identifier for Humans | Supervised by Associate Professor Waleed Abdulla and Associate Professor Akshya Swain
- Novel Deep Learning Models for Automated Analysis of OCT Images in Ophthalmology | Supervised by Associate Professor Waleed Abdulla and Associate Professor Akshya Swain
- Fingerprint Template Protection using Compact Minutiae Patterns | Supervised by Associate Professor Waleed Abdulla and Dr. Mark Andrews
- Progressive Compression of 3D Mesh Geometry Using Sparse Approximations from Redundant Frame Dictionaries | Supervised by Associate Professor Waleed Abdulla
- Automatic Retinal Image Analysis to Triage Retinal Pathologies | Supervised by Associate Professor Waleed Abdulla and Associate Professor Akshya Swain
- Botanical Origins Classification and Adulteration Detection in NZ Honey using Machine Learning and Hyperspectral Imaging | Supervised by Associate Professor Waleed Abdulla
- Multi-agent based Ambient Intelligence Platform | Supervised by Associate Professor Waleed Abdulla and Professor Zoran Salcic
Scholarships and awards
There are several scholarships you may be eligible for when you decide to pursue your PhD in Computer Systems Engineering, including the University of Auckland Doctoral Scholarships.
Help and advice
For general student enquiries, please contact a Student Hub.
If you would like to find out more about studying Computer Systems Engineering, you can contact a Postgraduate Adviser.