Background

Our AI staff members have a wide variety of research interests; the list below gives a high-level overview that is intended to be helpful for potential students (PhD, MSc, COMP501+589, AIML501+589, Directed Individual Study) in understanding who they may want to work with.

You are much more likely to get a positive response if you describe why you are interested in working with somebody. It is even better to suggest a project/research idea that matches their interests.

Not all staff members have the capacity to take on all new students at any given time --- this may be indicated below. Please respect staff by not contacting more than 1-3 staff members at once (we get enough emails as it is!).

• A/Prof Peter Andreae: not accepting new students.
• Dr Aaron Chen
  Interests: Deep reinforcement learning theories and algorithms, applications of deep reinforcement learning to a broad range of problems, such as cloud resource allocation, workflow scheduling and other combinatorial optimization problems. Multi-agent systems, multi-agent deep reinforcement learning and their applications to dynamic scheduling and resource allocation problems. Evolutionary computation for combinatorial optimization (e.g., genetic programming hyper-heuristic for job shop scheduling and cloud workflow scheduling) and deep learning (e.g., evolutionary neural architecture search).
  Availability:I am available to take on new students who match my interests.
• Dr Qi Chen
  Interests: AI and Machine Learning, particularly in genetic programming, symbolic regression and modelling, computer vision and image analysis, feature selection and dimensionality reduction.
  Availability: I am available to take on new students who match my interests.
• Kirita-Rose Escott:
  Interests: Applications of evolutionary computation (e.g., genetic programming hyper-heuristic) and machine learning (e.g., deep reinforcement learning and multi-agent systems) to combinatorial optimization problems, such as resource allocation and workflow scheduling in cloud computing.
  Availability: Not accepting new students.
• A/Prof Marcus Frean
  Interests: (i) fundamentals / game theory underlying origin of cooperation in complex systems (e.g. reputations, memory and the origin of money); (ii) machine learning, especially probabilistic inference using neural nets.
  Availability: able to take on new students who match my interests.
• A/Prof Xiaoying Sharon Gao
  Interests: My main research areas are natural language processing, Web intelligence and evolutionary computation. My current focus is text classification and clustering, and I have projects on using machine learning to develop multi-view text representations, and using Genetic Programming to learn neural network architectures for text classification.
  Availability: I am available to take on new students who match my interests.
• Dr Heitor Gomes
  Interests: My research mainly involves the creation of novel machine learning algorithms for streaming data. I am particularly interested in partially labelled data (semi-supervised learning), ensemble learning, and drift detection methods. More recently, alongside my students, I've started exploring continual learning problems using neural network approaches. I often supervise students in applied data science projects (particular interest in the energy sector), exploring the research topics mentioned above (and others) to solve challenging problems.
  Availability: I am available to take on new students who match my interests.
• Prof Bastiaan Kleijn
  Interests: Methods that form the basis of the latest machine-learning advances, such as ChatGPT and Stable Diffusion. Examples are generative methods (diffusion, normalising flows, GANs), continuous representations of neural networks, and the mathematics that is required to understand these methods. Applications of deep-learning to a broad range of areas including reinforcement learning, gaming, geophysics, acoustics, speech.
  Availability: I am available to take on new students who match my interests.
• Prof Ali Knott
  Interests: (i) Computational models of brain function, especially for human language and its connection to the sensorimotor system. This includes recent AI models using transformers. (ii) Social impacts and ethics of AI, and AI oversight / regulation. A particular interest at present is regulation of social media platforms.
  Limited availability at present, but I'm happy to discuss projects in these areas.
• Dr Andrew Lensen
  Interests: primarily explainable AI, genetic programming, unsupervised learning (manifold learning), and real-world/interdisciplinary AI in NZ. I am also interested in the social and ethical implications of AI and aspects of deep learning, such as embedding/dimensionality reduction methods.
  Availability: I am available to take on new students who match my interests.
• A/Prof Hui Ma
  Interests:social network analysis, service composition, service deployment, dynamic workflow scheduling, and resource allocation in cloud computing, and other combinatorial optimization problems, using Evolution Computation and other AI techniques.
  Availability: I am available to take on new students who match my interests.
• A/Prof Yi Mei
  Interests: (1) AI and machine learning for solving real-world optimisation problems, such as delivery pathfinding, ambulance dispatching, nurse rostering. (2) Genetic Programming. (3) Explainable AI. (4) Multi-objective Optimisation and Decision Making. (5) Automatic Algorithm Design. (6) Transfer/Multi-task Learning and Optimisation. (7) Reinforcement Learning.
  Availability: I am available to take on new students who match my interests.
• Dr Bach Nguyen
  Interests: Machine Learning, Classification, Evolutionary Machine Learning, Feature Selection, Feature Construction, Dimensionality Reduction, Transfer Learning and Domain Adaptation, Particle Swarm Optimisation, Differential Evolution, Evolutionary Multi-objective Optimisation/Learning.
  Availability: I am available to take on new students who match my interests.
• Kevin Shedlock
  Interests: (1) Fuzzy inference systems applied as a computational technique used to model reason about uncertain or imprecise information (2) Indigenous Socio-Technical System as a supervised setting of classification for cultural decision-making.
  Availability: I am available to take on new students who match my interests.
• Prof Bing Xue
  Interests: Machine Learning, Data Mining, Computer Visions and their real-world applications, particularly Evolutionary Machine Learning, Genetic Programming, Explainable AI and Interpretable Machine Learning, Feature Selection/Construction/Extraction, Dimension Reduction, Transfer Learning and Domain Adaptation, Multi-task Learning, Evolutionary Multi-objective Optimisation/Learning, Evolutionary Deep Learning, and Evolving Deep Neural Netrowks.
  Availability: I am available to take on new students who match my interests.
• Prof Mengjie Zhang
  Interests: Artificial Intelligence and Machine Learning, particularly in genetic programming, modelling and symbolic regression, computer vision and image analysis, deep learning and transfer learning, feature selection and big dimensionality reduction, and AIML applications to primary industry, climate change and health outcome.
  Availability: I am available to take on new students who match my interests.