university of auckland phd computer science

Associate Professor

Jing Sun Profile page

• Associate Professor School of Computer Science
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Jing completed his PhD study in Computer Science from National University of Singapore in June 2003 and joined the Department of Computer Science at The University of Auckland in August 2003, who is now an Associate Professor. Distinctions/Honours: New Zealand Business Events Award, Tourism New Zealand, recognised by Minister of Tourism (Hon Kelvin Davis), October 2018. Responsibilities: PhD Coordinator, School of Computer Science, The University of Auckland. Committee/Professional groups/Services: Editorial Board Member: - Innovations in Systems and Software Engineering, A NASA Journal (ISSE), Springer. Steering Committee Member: - IEEE International Conference on Engineering of Complex Computer Systems (ICECCS) Program Committee Chairs: - 24th International Conference on Engineering of Complex Computer Systems (ICECCS 2019), Guangzhou, China, 10-13 Nov 2019. (A ranked by CORE) - 20th International Conference on Formal Engineering Methods (ICFEM 2018), Gold Coast, Australia, 12-16 November 2018 (B ranked by CORE). - 22nd Asia-Pacific Software Engineering Conference (APSEC 2015), New Delhi, India, 1-4 December 2015. (B ranked by CORE) - 15th International Conference on Formal Engineering Methods (ICFEM 2013), Queenstown, New Zealand, 29 October - 1 November 2013 (B ranked by CORE). - 12th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS'07), Auckland, New Zealand, 11-14 July, 2007. (A ranked by CORE) Chair of Local Organization Committee: - 18th International Conference on Semantic Web (ISWC 2019), Auckland, New Zealand, 26-30 October 2019. (A ranked by CORE) Qualifications: Ph.D. (01/2000 - 06/2003), Department of Computer Science, National University of Singapore. Areas of Expertise: Software Engineering, Formal Methods, Computer Aided Verification, Model Checking, Automated Reasoning, Theorem Proving, Software Automation. Media Keywords: Computer languages, formal specification, Checking models, Specification validation, Theorem proving, Unified modelling language, Web semantic, Environments and methodologies for software development, Software Quality Assurance.

UNIVERSITY OF AUCKLAND APPOINTMENTS

• Associate Professor Faculty of Science, School of Computer Science, New Zealand

ACADEMIC POSITIONS

• Associate Professor The University of Auckland, Computer Science, Auckland, New Zealand 1 Feb 2016 - present
• Senior Lecturer The University of Auckland, Computer Science, Auckland, New Zealand 1 Feb 2007 - 1 Feb 2016
• Lecturer The University of Auckland, Computer Science, Auckland, New Zealand 3 Aug 2003 - 1 Feb 2007
• PhD National University of Singapore, Singapore, Singapore 1 Jan 2000 - 3 Jun 2003

FACULTY / INSTITUTE

• Faculty of Science

GRADUATE SUPERVISION

• PhD/Doctoral Accredited Supervisor
• Has Current Supervision Opportunity

MEDIA ENQUIRIES

• Available for media enquiries

FIELDS OF RESEARCH

• Software engineering
• Automated software engineering
• Formal methods for software
• Software architecture
• Software testing, verification and validation
• Software quality, processes and metrics
• Software and application security

• PUBLICATIONS
• CODE LIBRARY

Group Members

We are looking for new PhD students, Postdocs, and Master students to join the team!

Lab Director

Senior Lecturer Email: [email protected] Bio: Jiamou Liu is a Senior Lecturer at the School of Computer Science, The University of Auckland. He was a Senior Lecturer at Auckland University of Technology between 2011 and 2015. Jiamou obtained a PhD in Computer Science from the University of Auckland, and worked as a research associate in University of Leipzig between 2009 and 2010 and Paris Diderot University (Paris 7) in 2013. He was a research intern at Microsoft Research Asia in 2008. During his PhD, he was a visiting student at Cornell University and National University of Singapore. Originally trained as a theoretical computer scientist, Jiamou’s current research is in Artificial Intelligence. He is interested in both the theoretical and the applied aspects of artificial intelligence. In particular, his work revolves around the structural analysis and algorithmic studies of social networks, multiagent systems, machine learning, as well as natural language processing. His recent research also connects to health-care, real estate data mining, data privacy, computational social science, and spatial-temporal data analysis with application in traffic flow prediction.

PhD Students

2020.02 – Present Email: [email protected] Bio: Qiming received a Bachelor of Science (Honours) degree with First Class Honours in Computer Science from the University of Auckland in 2019. His research interests lie in the intersection between natural language processing and question answering. Recently his research mainly focuses on machine reasoning. His main research activities involve natural language understanding, natural language inference, and soft reasoning; topics of interest include problem decomposition, knowledge acquisition, explanation, entailment, and generate QA. He is also interested in the graph-based neural network.

Pengqian Han

2021.10 – Present Email: [email protected] Bio: I got my master’s degree in aeronautical engineering from Beihang University in 2018 and got my bachelor’s degree from Hebei University of Technology in 2014. I have been an engineer in China Mobile Group Tianjin Company from 2018 to 2021. My main research interests are machine learning, deep learning, and graph-based neural network.

2020 – Present Email: [email protected] Bio: Weidong received a degree of Bachelor of Science (Honours) with First Class Honours in Computer Science from the University of Auckland in 2019. She received a Bachelor of History from Capital Normal University in 2013. Her research interests include social network analysis, multi-agent systems and reinforcement learning.

Xiaoxuan Li

2020 – Present Email: <> Bio: I received my honours (First Class) degree in computer science from The University of Auckland in 2019 and received my bachelor’s degree from The Tianjin University of Technology in 2015. My primary scientific interests focus on exploring Natural Language Process (NLP) technology to facilitate Robotic Process Automation (RPA), in particular in discovering business process flow from natural language texts.

2019. 11 – Present Email: [email protected] Bio: I received my bachelor of mathmatics and master of engineering from Beijing Institute of Technology. My major interest lies in the network structures and dynamics. Recently my research focuses on the core/periphery structures. I am also interested in the theoretical analysis of machine learning, graph-based neural network, and so on.

2020 – Present Email: [email protected] Bio: Lin Ni, a practitioner and academic, is keen to turn AI technologies into concrete value. She received a B.E. degree from Northeastern University (China) in 2010, and a Postgraduate Diploma in Computer Science from the University of Auckland in 2017. She lands technologies and provides AI solutions to address the challenges in the industry, dabbled in Car Navigation systems, Recommendation systems, Multi-agent systems, and Natural Language Processing projects. Chatbots attract her focus in recent years, especially chatbots in the health and medical domain.

Qianqian Qi

2019.9 – Present Email: [email protected] Bio: I received my M.Sc. degree specialised in Communications and Signal Processing from Imperial College London in 2014, and my B.Eng. degree major in Electronic and Information Engineering from Dalian University of Technology in 2013. After that, I worked as a software engineer in Singapore for more than 4 years. I am now doing research in the field of Natural Language Processing, mainly on natural language understanding and generation.

To start PhD Email: <> Bio: I received my master degree in computer science from Southwest University in 2019 and bachelor degree from Chongqing Normal University in 2016. My research interests include social network analysis, opinion dynamic, multi-agent systems and deep learning.

2020 – Present Email: <> Bio: I received my master degree in computer science and technology from the Beihang University in 2020, and bachelor in software engineering from Dalian University of Technology in 2017. My main research interests are machine learning and deep learning, especially Graph-based models and Self-supervised models. Recently, I am focused on constructing hybrid models combining anchor-based graph and neural networks to solve real-world problems with Self-supervised learning.

2019.12 – Present Email: [email protected] Bio: I received both my Honours (First Class) and Bachelor of Science Degrees in Computer Science from The University of Auckland. My main research interest lies in network structures, optimization problems, and discrete space evaluation and optimization. Recently, I am focused on core-periphery network structures.

2019.12 – Present Email: [email protected] Bio: I got my master degree of computer science from the University of Auckland in 2018 and got my bachlor degree from Nanjing University in 2016. My main research interests are machine learning, deep learning, graph-based neural network and computer vision. I also do reserach related to artificial intelligence in healthcare and software engineering.

2022.02 – Present Email: [email protected] Bio: I received a degree of Master of Professional Studies with First Class Honours in Data Science, the Graduate Diploma in Science from the University of Auckland in 2021, and the Bachelor degree from the Southwest University in 2020. My personal research interests lie in the reinforcement learning and the multi-agent systems. In detail, I am interested in the challenges in both cooperative and non-cooperative settings in adapting reinforcement learning to multi-agent systems.

Xianda Zheng

2022.10 – Present Email: [email protected] Bio: Xianda received M.Eng degree in Computer Science from Southeast Univercity in 2021 and received B.Eng degree in Computer Science from Changchun University of Science and Technology in 2018. His research interests include Knowledge Graph representation learning and reasoning.

Zijian Huang

2023.04 – Present Email: [email protected] Bio: I received both my Master of Science (First Class) and Bachelor of Science degrees in computer science from the University of Auckland. My primary research interests include knowledge graph representation learning, multi-hop query reasoning over knowledge graphs, and natural language question answering.

2018.09 – 2023.07 Email: [email protected] Bio: I received my bachelor degree from Wuhan Institute of Technology and master degree from Wuhan University of Technology. I have been a lecturer in Guangdong University of Petrochemical Technology from 2015 to 2018. My research interests include social network analysis, especially network embedding.

2018. 08 – 2023. 04 Email: [email protected] Bio: I received both my Honours (First Class) and Bachelor of Science Degrees in Computer Science from The University of Auckland. My research interests lie broadly in Natural Language Processing with my recent research focusing on the intersection between Psychology, Artificial Intelligence and Natural Language Processing.

2018. 11 – 2022. 04 Email: [email protected] Bio: I am currently a research fellow with the School of Computer Science, The University of Auckland . I obtained my PhD in computer science from The University of Auckland , where I was supervised by Dr. Jiamou Liu and Prof. Bakhadyr Khoussainov . I received the First Class Honours degree in computer science from The University of Auckland in 2018. Before coming to New Zealand, I received the B.S. in computer science from Beijing Institute of Technology in 2017. My research interests span a spectrum of (inverse) reinforcement learning, computational game theory and multi-agent systems. Lately, my research focus is on applying reinforcement learning in large-scale multi-agent games, natural language processing and automatic reasoning. When I am not spending time on research and teaching, I can be found as a hiker and photography lover. I have hiked to many famous routes in many cities and towns across China and New Zealand. The collections of pictures that I took in the hike-way can be found in my personal online gallery .

Mengxiao Zhang

2017. 04 – 2021. 11 Email: [email protected] Bio: I hold Bachelor’s degree of Management in Information Management and Information Systems and Master’s degree of management in Management Science and Engineering. My research interests are algorithmic mechanism design and economics of security and privacy. My current research focus is incentive mechanisms for data pricing and privacy preservation.

Sajjad Hassanpour

Email: [email protected] Bio: Sajjad Hassanpour is a Ph.D. student in Construction Engineering at the University of Auckland. He received a bachelor’s degree in civil engineering at Iran University of Science and Technology in 2010, and his M.Sc. degree in transportation planning-at the Trabiat Modares University of Iran in 2012. During his Ph.D. in transportation planning, as he was interested in computer science, he started working on agent-based modeling and computer-based simulation models. Therefore, he started a new Ph.D. at the University of Auckland, focusing on agent-based building earthquake evacuation simulation. He is interested in pedestrian dynamics, multiagent systems, and machine learning.

© 2023 LIU AI LAB.

We are part of the School of Computer Science at University of Auckland .

COMPSCI 389 : Research Methods in Computer Science

2022 semester two (1225) (15 points), course prescription, course overview.

This course is an overview of research methods and techniques used across Computer Science, including formal proof techniques and empirical methods that involve quantitative and/or qualitative data. Students will be expected to apply the research methods approach to develop a research proposal for a Computer Science research topic of their choice. Students will investigate a computing topic relevant to social or environmental responsibility in groups. The course finishes with a debate on a topic pertinent to the discipline.

Course Requirements

Capabilities developed in this course, learning outcomes.

• Describe the most common and well-established research methods employed in computer science research (Capability 1)
• Write an effective and feasible research proposal (Capability 1, 2, 3 and 5)
• Formulate an original and sound argument with scientific claims that are effectively supported by empirical evidence and/or formal constructions (proofs) (Capability 1, 2 and 5)
• Use electronic systems of bibliographic citation (Capability 1 and 5)
• Engage effectively in a peer-review review process of a piece of computer science research, both as a reviewer and reviewee (Capability 1 and 2)
• Engage productively in collaborative research that engages with a set of collaborators that is diverse culturally and/or in their areas of expertise on a topic relevant to social or environmental responsibility. (Capability 1, 3, 4, 5 and 6)
• Effectively communicate the results of a research project, by way of a poster and or presentation. (Capability 4 and 5)

Assessments

Special requirements.

Not applicable

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course you can expect 24 hours of contact hours, 82 hours assignments and test preparation, and 44 hours self-directed learning.

Delivery Mode

Campus experience.

Attendance is expected at scheduled activities including tutorials to complete components of the course. Lectures will be available as recordings. Other learning activities including seminars/tutorials will not be available as recordings. The course will include live online events including group discussions/tutorials. Attendance on campus is required for the test. The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html .

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html .

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

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Computer Science and Software Engineering department

Ranked highly around the world, the Computer Science and Software Engineering department is part of engineering, computer and mathematical sciences at AUT, and offers a wide range of undergraduate and postgraduate programmes.

Undergraduate study in computer science and software engineering will give you a solid grounding in this area.

• Bachelor of Computer and Information Sciences
• Bachelor of Engineering (Honours) in Software Engineering

The Computer Science and Software Engineering department offers a range of postgraduate degrees:

• Bachelor of Science (Honours)
• Postgraduate Certificate in Computer and Information Sciences
• Postgraduate Diploma in Computer and Information Sciences
• Master of Computer and Information Sciences
• Master of Cyber Security and Digital Forensics
• Master of IT Project Management
• Master of Philosophy
• Doctor of Philosophy

Research in computer science and software engineering

We believe in high-quality research that has impact, and have world-class researchers and research strengths across engineering, computer and mathematical sciences.

International partnerships

Engineering, computer and mathematical sciences at AUT have a number of international partnerships and collaborative programmes with other universities.

Undergraduate Phone: +64 9 921 9999 ext 5857

[email protected]

Postgraduate Phone: +64 9 921 9999 ext 5123

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Graduate Diploma in Science - Computer Science

This course is available

Level of Study

Graduate Certificate or Diploma

Next start date

Expected Mar 2025

Grafton Campus

The Graduate Diploma in Science will extend the knowledge and expertise gained from your Bachelor of Science degree.

The GradDipSci provides you with an opportunity to choose a second major, extend the field of study you chose for your Bachelor of Science degree, or continue to learn from another discipline at undergraduate level within the Faculty of Science. The GradDipSci also provides a pathway to enter into further study at postgraduate level.

Programme structure

To complete this programme you need to pass courses totalling 120 points. Courses are typically worth 15 points.

At least 75 points (five courses) must be at Stage III or above, from the Bachelor of Science or Bachelor of Science (Honours) schedules.

At least 60 points must be from a subject major listed in the Bachelor of Science schedule, and this must include the Stage III courses required for the major.

A project or dissertation of up to 30 points may be included if approved prior to enrolment.

Please see the University of Auckland Calendar Regulations for the Graduate Diploma in Science.

You'll also need to meet other requirements, including time limits and total points limits. See Postgraduate enrolment.

Where could this programme take you?

Because science plays a vital role in addressing the key issues that confront us and future generations, studying the Sciences opens up a wide range of career opportunities. If you have been away from study for a while, the GradDipSci provides an opportunity to learn about new developments in your field of expertise.

Further study options

Postgraduate Diploma in Science

Master of Science

Doctor of Philosophy

Entry criteria

You must have completed an undergraduate degree in science at a recognised university (or similar institution) and passed first-year courses in your intended specialisation.

A GPA/GPE of at least 3.0 is strongly recommended

You can still gain entry if you have gained the equivalent level of competence through work experience or a professional qualification.

IELTS (Academic): Overall score of 6.0 and no bands below 5.5; Internet based TOEFL (iBT): Overall score of 80 and a written score of 21; Paper-based TOEFL: Overall score of 60 and a writing score of 21; Cambridge English: Advanced (CAE), Cambridge English Proficiency (CPE): Overall score of 169 and no bands below 162; Foundation Certificate in English for Academic Purposes (FCertEAP): Grade of C-; Pearson Test of English (PTE) Academic: Overall score of 50 and no PTE Communicative score below 42; Michigan English Language Assessment Battery (MELAB): 80.

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• 10 April 2024

Randomness in computation wins computer-science ‘Nobel’

• Davide Castelvecchi

You can also search for this author in PubMed   Google Scholar

Avi Wigderson received the Turing Award for his foundational contributions to the theory of computation. Credit: Dan Komoda

A leader in the field of computational theory is the latest winner of the A. M. Turing Award, sometimes described as the ‘Nobel Prize’ of computer science.

Avi Wigderson at the Institute for Advanced Study (IAS) in Princeton, New Jersey, is known for work straddling several disciplines, and had already won a share of the Abel Prize , a top mathematics award, three years ago.

He receives the Turing Award “for foundational contributions to the theory of computation, including reshaping our understanding of the role of randomness in computation, and for his decades of intellectual leadership in theoretical computer science”, the Association for Computing Machinery (ACM) in New York City announced on 10 April.

“I was extremely happy, and I didn’t expect this at all,” Wigderson tells Nature . “I’m getting so much love and appreciation from my community that I don’t need prizes.”

‘A towering intellectual force’

Wigderson was born in Haifa, Israel, in 1956. He studied at Technion — Israel Institute of Technology in Haifa and later at Princeton University; he has been at the IAS since 1999. He is known for his work on computational complexity — which studies how certain problems are inherently slow to solve, even in principle — and on randomness in computation. Many practical algorithms make random choices to achieve their objectives more efficiently; in a series of groundbreaking studies in the 1990s, Wigderson and his collaborators showed that conventional, deterministic algorithms can, in principle, be roughly as efficient as ‘randomized’ ones 1 . The results helped to confirm that random algorithms can be as accurate as deterministic ones are.

“Wigderson is a towering intellectual force in theoretical computer science,” said ACM president Yannis Ioannidis in a statement. In addition to Wigderson’s academic achievements, the ACS cited his “friendliness, enthusiasm, and generosity”, which have led him to be a mentor to or collaborate with hundreds of researchers worldwide. Wigderson admits that he is a “big proselytizer” of the intellectual pleasures of his discipline — he wrote a popular book about it and made it freely available on his website . “I think this field is great, and I am happy to explain it to anybody.”

The Turing Award is named after the celebrated British mathematician and code-breaker Alan Turing (1912–54), who in the 1930s laid the conceptual foundations of modern computing. “I feel completely at home with mathematics,” says Wigderson, adding that as an intellectual endeavour, theoretical computer science is indistinguishable from maths. “We prove theorems, like mathematicians.”

doi: https://doi.org/10.1038/d41586-024-01055-y

Impagliazzo, R. & Wigderson, A. in Proc. 29th ACM Symposium on Theory of Computing 220–229 (ACM, 1997).

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University of Auckland excels in 2024 QS subject rankings

10 April 2024

University news , Faculty of Science , Faculty of Arts , Faculty of Engineering , Faculty of Education and Social Work

The University's research, reputation and teaching is having a global impact, with ten subjects it teaches ranked in the top 50 subjects of universities worldwide.

Waipapa Taumata Rau, University of Auckland has added to its reputation as a world-leading research, teaching and learning institution, with its results in the QS World University Rankings by Subject 2024.  

Ten of the subjects the University teaches have been ranked in the top 50 subjects worldwide, based on academic and employer reputation as well as research, compared with eight in 2023. In the top 100, the University has 23 ranked subjects.  

Marketing ranks 21-50 in the world, entering the top 50 for the University for the first time. Anatomy and Physiology is also a new entrant to the QS top 50 subjects, ranking 45=.  

Sports related subjects, regularly in the top 50, are equal 28th, up from 32 in 2023. Education, consistently in the top 50, holds firm at 37, while Archaeology ranks 39th equal, up from 46 in 2023.  Anthropology, ranked 48, is up one place from 2023. Rounding out the other ten in the top 50 subjects are Civil Engineering (46) and English (48). Two subjects that had fallen out of the top 50 last year are back in – Psychology (45) and Linguistics (49).

The 2024 QS Subject Rankings comprise a research component but also a strong employer reputation component.

Professor Jason Ingham, who was head of the Department of Civil and Environmental Engineering during the rankings period, says the QS Subject Rankings are important for many reasons.

“When we advertise to fill vacant academic appointments, they help us to receive the strongest applicants – people who recognise the reputation of the University of Auckland. They’re also important to attract high-calibre doctoral students from around the world.”

He says being able to say a subject offering is ‘among the best in the world’ is invaluable.

Professor Frank Bloomfield, Deputy Vice-Chancellor Research, says it’s heartening to know that people recognise the University as being a leading university globally.

“For staff to know that the research and research-led teaching they do is highly valued by their international peers is empowering. Having ten subjects ranked in the top 50 in the world reflects the quality of our research and teaching and contributes to University of Auckland degrees being recognised globally.”

He says in research, academics and students are making significant strides in addressing some of the world's most pressing challenges, from climate change to healthcare disparities.

“Our interdisciplinary approach fosters collaboration and innovation and we’re developing solutions that resonate globally. Our students know the importance of this kind of work."

For staff to know that the research and research-led teaching they do is highly valued by their international peers is empowering.

Professor Frank Bloomfield Deputy Vice-Chancellor Research

Vice-Chancellor Professor Dawn Freshwater said the results emphasised the University’s commitment to excellence and innovation, and the role staff play in showcasing research and best practice in teaching and learning.

“The University is dedicated to providing students with a world-class education that prepares them for success in an ever-changing world,” she said. “Our goal is to foster a culture of curiosity, creativity and critical inquiry to empower students to become lifelong learners and leaders in their respective fields. We’re doing that really well.”

The methodology for the QS subject rankings used saw 45 of the University’s subjects meet the criteria to be ranked, and 23 of those were ranked in the top 100 in the world.

In November 2023, eight University of Auckland-affiliated researchers were named in the prestigious Clarivate Highly Cited Researchers List , and this month, six of the University’s researchers were elected Fellows by the Royal Society Te Apārangi .

About the QS Subject Rankings 

The 2024 edition of the QS World University Rankings by Subject , released on 10 April by global higher education analyst QS Quacquarelli Symonds, provides independent comparative analysis on the performance of more than 16,400 individual university programmes, taken by students at more than 1,500 universities in 96 locations around the world, across 55 academic disciplines and five broad faculty areas. 

Other current rankings

The University of Auckland was ranked 68th in the world in the overarching QS World University Rankings 2024, making it New Zealand’s highest-ranked university. It was also ranked fifth in the world in the  2024 QS World University Sustainability Rankings. The University was ranked No. 1 in New Zealand and 68th worldwide in the QS Graduate Employability Rankings in 2023. 

For more information: 

University of Auckland Media Manager Denise Montgomery denise.montgomery@auckland.ac.nz

Related links

• New Zealand's world-ranked University
• University applauds researchers with global reach and impact

Michael Bunn Profile page

• Lecturer Engineering, Computer and Mathematical Sciences
• [email protected]

A lecturer with a diverse background to prior to academia, having worked as an Avionics Technician for approximately ten years and a further eight in the telecommunications industry. A subject matter expert in both power and electronic engineering with a particular focus on embedded systems and the practicalities of designing and building electronic projects.

ACADEMIC POSITIONS

• Lecturer Auckland University of Technology, Electrical and Electronic Engineering, Auckland, New Zealand 16 Feb 2024
• PhD Auckland University of Technology, Auckland, New Zealand 28 Jul 2022
• Bachelor of Engineering (First Class Honours) Auckland University of Technology, Auckland, New Zealand 27 Jul 2017
• English Can read, write, speak, understand and peer review

AVAILABILITY

• Masters Research or PhD student supervision
• Industry Projects
• Collaborative projects
• Technical support
• Teaching provision

FIELDS OF RESEARCH

• Power and Energy Systems Engineering (excl. Renewable Power)
• Renewable Power and Energy Systems Engineering (excl. Solar Cells)
• Energy Generation, Conversion and Storage Engineering
• Electrical and Electronic Engineering

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ECEE Awards Dinner 2024

Please join us as we celebrate our faculty and student award winners — as well as all of our students, faculty and staff who contributed to a successful school year!

Friday, April 26, 2024 7 p.m.

Williams Village Center Dining & Community Commons Multipurpose Room 

All ECEE faculty, staff, graduate students, graduating seniors and award winners are invited. Graduating seniors are welcome to bring their parents/guardians, and faculty, staff and graduate students may bring a plus-one. Dinner and other refreshments will be served. 

Please RSVP below. 

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Departments

• Ann and H.J. Smead Aerospace Engineering Sciences
• Chemical & Biological Engineering
• Civil, Environmental & Architectural Engineering
• Computer Science
• Electrical, Computer & Energy Engineering
• Paul M. Rady Mechanical Engineering
• Applied Mathematics
• Biomedical Engineering
• Creative Technology & Design
• Engineering Education
• Engineering Management
• Engineering Physics
• Environmental Engineering
• Integrated Design Engineering
• Materials Science & Engineering

Affiliates & Partners

• ATLAS Institute
• BOLD Center
• Colorado Mesa University
• Colorado Space Grant Consortium
• Discovery Learning
• Engineering Honors
• Engineering Leadership
• Entrepreneurship
• Herbst Program for Engineering, Ethics & Society
• Integrated Teaching and Learning
• Global Engineering
• Mortenson Center for Global Engineering
• National Center for Women & Information Technology
• Western Colorado University