Members

The Machine Learning Group at the University of Auckland is the the biggest research group of the School of Computer Science. Our research covers diverse machine learning topics, carried out in a high number of theoretical and applied machine learning projects. We have strong experience in helping researchers use the full potential of their data using innovative machine learning techniques. Our research is published in the top machine learning conferences and journals.
Joerg Simon Wicker

Joerg Simon Wicker

Director - Senior Lecturer

My main research area is machine learning and its application to bioinformatics, cheminformatics, and computational sustainability. Before joining the University of Auckland in 2017, I did a PostDoc at University of Mainz, Germany, and a PhD at Technical University of Munich, Germany. My current research focuses on diverse areas ranging from reliability of machine learning algorithms, particularly in respect to adversarial learning and bias to applications in epidemology, chemistry, environmental research, and cybersecurity.

Yun Sing Koh

Yun Sing Koh

Associate Professor

Yun Sing Koh is an Associate Professor at the School of Computer Science, The University of Auckland, New Zealand. Her research is in the area of machine learning. Within the broad research realm, she is currently focusing on: data stream mining, lifelong and transfer learning, anomaly detection, and pattern mining. She has published more than 100 research papers in this field at top venues. She is passionate about pushing the boundaries of fundamental machine learning research and applying it to interdisciplinary areas such as environmental science and healthcare.

Michael Witbrock

Michael Witbrock

Professor

Michael is building a research group, the Broad AI Lab, at the intersection of machine learning, reasoning and natural language understanding, with an additional focus on achieving the best social and civilizational impacts of increasingly powerful AI.

Jiamou Liu

Jiamou Liu

Senior Lecturer

Jiamou Liu is a Senior Lecturer at the School of Computer Science, The University of Auckland. Before joining the UoA, 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. In particular, his work revolves around the structural analysis of social networks, multiagent systems, as well as natural language processing. His recent research also connects to health-care, data privacy, computational social science, and spatial-temporal data analysis with application in traffic flow prediction.

Thomas Lacombe

Thomas Lacombe

Professional Teaching Fellow

My research interests are wide and various, centring on the application of machine learning and data mining to a wide range of fields such as data streams, image processing and computer vision. I have previously worked in industrial computer vision and machine learning applied to develop visual quality control for plastic injection production lines. More recently, I focused on automated hyper-parameter setting in a data stream environment.

I like to stay adaptable to broaden my expertise and I am especially motivated to work on interdisciplinary and applied projects.

Yang Chen

Yang Chen

Research Fellow

Yang worked in the area of (inverse) reinforcement learning and computational game theory during his PhD study in the University of Auckland. He received his First Class Honours degree in computer science from the University of Auckland in 2018. He obtained his B.S. in computer science from Beijing Institute of Technology in 2017. During his PhD, he was a research intern at DAMO Academy (Alibaba) in 2020. He also got the Google Global PhD Fellowship Nomination in 2020. Currently his research focus is on applying reinforcement learning to automatic reasoning and proving.

Kaiqi Zhao

Kaiqi Zhao

Lecturer

I have broad research interests in general topics of big data analytics, data mining and machine learning. Particularly, I am specialized in spatio-temporal data mining, text mining and recommender systems. In my recent research, I have worked on probabilistic generative models and deep generative models for mobility modeling and recommendations on spatio-temporal data such as GPS trajectories, location-based check-ins and geo-tagged tweets. I have also worked on efficient and effective topic mining algorithms for big spatio-temporal data.

Daniel Wilson

Daniel Wilson

Professional Teaching Fellow

My academic training is in both philosophy and data science and I have research interests at the intersection of these domains, particularly with respect to professional ethics and socially responsible use of AI and ML. I also investigate privacy techniques employed in the public release of personal information, specifically with respect to confidentiality and usability. I am a member of Te Pokapū, the steering committee of Te Mana Raraunga – the Māori data sovereignty network

Katerina Taskova

Katerina Taskova

Lecturer

My main research lies in the intersection of machine learning, meta-heuristic optimization, mathematical modeling, and data science with major applications in the filed of biology, ecology, engineering and social sciences. My work is strongly motivated by real-life problems that can benefit from data-driven modeling and automated modeling approaches exploiting both domain-specific knowledge and different types of measured data as relevant for systems sciences.

Jason Tam

Jason Tam

Honorary Academic

Having started my academic training in Physics that eventually led to handling and analysing huge datasets, my main research interests naturally fall into how applications of advanced data science techniques, including ML and AI, can help transform workflows in scientific and technical disciplines for the future. Having previously applied modern data science tools and techniques in various aspects, from IoT and cloud technologies to custom analytics and visualizations, in disciplines such as Civil Engineering, Seismology and Environmental Science, currently I am mainly focused on improving predictions of chemical reactions in Environmental Chemistry.

I like to stay adaptable to broaden my expertise and I am especially motivated to work on interdisciplinary and applied projects.

Alex Peng

Alex Peng

Research Fellow

Alex was a commerce graduate who found his passion in artificial intelligence, especially in machine learning. His PhD thesis is on improving the generalisation of neural networks when labelled data is limited by utilising unlabelled data. Currently, his research focuses on NLP tasks and automated reasoning with neural networks. His other personal research interests include trying to understand the generalisation of neural networks, causal inference from data and symbolic regression.

Gill Dobbie

Gill Dobbie

Professor

Gill has a wide range of research interests, including databases, the web, and software engineering. She is interested both in structured and semistructured data. More specifically, she is interested in how data can best be organized and managed, how the semantics of the data can be retained and expressed, and how querying can be carried out efficiently. Her main areas of interest pertain to databases and the web. She has worked in the foundations of database systems, defining logical models for various kinds of database systems, and reasoning about the correctness of algorithms in that setting. With colleagues at the National University of Singapore, she has defined a data model for semistructured data (called ORA-SS), providing a language independent description of the data. The group she was working with has used the ORA-SS data model to define a normal form for ORA-SS schema, defined valid views for semistructured databases, and described a storage structure for semistructured databases using object relational databases.

Pat Riddle

Pat Riddle

Senior Lecturer

My main research interests are in the AI areas of machine learning and datamining. In particular, I am interested in various techniques for machine learning (such as ensemble approaches, techniques which overcome overfitting problems, and data-engineering as incorporating background knowledge) and their applications to real world problems. In addition I have been working in the area of search, planning, and representation increasingly in the last few years.

David Tse Jung Huang

David Tse Jung Huang

Honorary Academic

Dr David Tse Jung Huang is an AWS Academy certified instructor working at the Auckland ICT Graduate School, the University of Auckland. David manages ICT short courses at the university and teaches into data science, machine learning, and cloud computing. He is an expert in applied machine learning and researches into change mining and analysis for big data and data streams. David is passionate about interactive teaching and keeping his students up-to-date with modern technology and theory. His most recent focus has been to upskill working professionals in machine learning and cloud computing.
Joshua Bensemann

Joshua Bensemann

Research Fellow

I am currently working in the field of artificial intelligence after completing a PhD in psychology. My research interests include incorporating concepts from psychology into deep learning as well as applying machine learning techniques to psychological data.

Diana Benavides Prado

Diana Benavides Prado

Senior Research Fellow

I am currently a Senior Research Fellow at the Strong AI Lab, School of Computer Science, The University of Auckland. My research focuses in the areas of Transfer Learning, Lifelong/Continual Learning and Human-Algorithm Collaboration. My applied experience includes leading the design and deployment of Machine Learning tools for supporting decision making in a variety of application domains. I have mentoring and teaching experience in Data Science, Machine Learning, Algorithms and Programming. I hold a PhD in Computer Science from The University of Auckland, New Zealand.

Students

Song Yang

Song Yang

PhD Student

Song Yang, a researcher and practitioner, is keen to turn machine learning technologies into real-world value. His research interests lie in Deep Learning, Graph Neural Networks, Spatio-temporal Data Mining, Computer Vision, and AI in Healthcare. Song Yang started his PhD in December 2019. Before that, he worked as a full-time machine learning engineer with several years of actual work experience. The computer vision/deep learning models he used to work on have been installed in several hospitals and clinics in New Zealand to detect lesions/diseases from medical images automatically. Recently, he is interested in the emerging field of Graph Neural Networks and applying GNNs on graph structure data.

Supervisor: Jiamou Liu and Kaiqi Zhao

Xinglong (Luke) Chang

Xinglong (Luke) Chang

PhD Student

Xinglong (Luke) Chang is a PhD student at the School of Computer Science,  the University of Auckland, New Zealand. His supervisors are Dr Joerg Simon Wicker and Professor Gillian Dobbie. His research interests are adversarial learning and security issues related to machine learning.

Supervisors: Gill Dobbie and Joerg Wicker

Qiming (Bill) Bao

Qiming (Bill) Bao

PhD Student

Qiming (Bill) Bao is a PhD student at the School of Computer Science, the University of Auckland, New Zealand. His supervisors are Professor Michael Witbrock and Dr Jiamou Liu. His research interests include soft reasoning related to deep learning.

Supervisors: Michael Witbrock and Jiamou Liu

Qianqian Qi

Qianqian Qi

PhD Student

I received my M.Sc. degree specialised in Communications and Signal Processing from Imperial College London in 2014, and my B.Eng. degree majoring 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 four years. I am now researching the field of Natural Language Processing, mainly on natural language understanding and generation.

Supervisors: Michael Witbrock

Yonghua Zhu

Yonghua Zhu

PhD Student

Yonghua Zhu is a PhD student at the School of Computer Science, the University of Auckland, supervised by Michael Witbrock and Bakhadyr Khoussainov. Currently, his research focuses on Natural Language Processing (NLP) in particular with reading comprehension of scientific papers.

Supervisors: Michael Witbrock and Bakhadyr Khoussainov

Tim Hartill

Tim Hartill

PhD Student

After graduating from the University of Auckland with a B.A in Computer Science and Philosophy in the 1980s, Tim spent over 30 years in industry before returning in 2020 to complete a BSc Honours degree. He is currently engaged in research on the topic of training NLP models to generalise to answering questions they have not encountered before.

Supervisors: Michael Witbrock and Pat Riddle

Nooriyan Poonawala-Lohani

Nooriyan Poonawala-Lohani

PhD Student

Influenza is a communicable respiratory illness that can cause serious public health hazards. Due to its huge threat to the community, accurate forecasting of Influenza-like-illness (ILI) can diminish the impact of an influenza season by enabling early public health interventions. Current forecasting models are limited in their performance, particularly when using a longer forecasting window. Commonly used methods to forecast ILI, including statistical methods such as ARIMA, limit prediction performance when using additional data sources that might have complex non-linear associations with ILI incidence. In my PhD, I use machine learning approaches to build models that can predict ILI cases more reliable further into the future.

Supervisors: Mehnaz Adnan, Pat Riddle, and Joerg Wicker

Jonathan Kim

Jonathan Kim

PhD Student

I am currently pursuing a PhD from the Department of Computer Science, while working as a Senior Research Engineer at Callaghan Innovation. I have a Master of Engineering Management(Hons) and Bachelor of Computer Systems Engineering, both from University of Auckland. My research involves achieving robust semantic scene understanding through joint optimisation of SLAM and DCNNs.

Supervisors: Pat Riddle and Joerg Wicker

Annie Lu

Annie Lu

PhD Student

I’m a machine learning PhD student from the department of computer science, the University of Auckland after I completed my Master of professional studies in Data Science. My research is regard with applying machine learning techniques for Growing Up in New Zealand to help obtain insights from longitudinal data.

Supervisors: Yun Sing Koh, Susan Morton, and Joerg Wicker

Neset Tan

Neset Tan

PhD Student

Before jumping into the Machine Learning research area, Neset involved research and teaching in Mathematics for a long period of time. He has worked a variety of academic and non-academic jobs such as a research assistant, post-doc researcher, lecturer, software engineer, founder, and director of an engineering consultant company. His current interest is positioned at the intersection of natural language progressing and automation of data science. He has been researching various approaches such as deep learning and reinforcement learning techniques to obtain efficient ML systems for the mentioned areas. He has several publications in functional analysis, measure theory, optimization theory, and numerical analysis.

Supervisors: Michael Witbrock

Stefan Fuchs

Stefan Fuchs

PhD Student

Stefan Fuchs is a PhD student at the University of Auckland, School of Computer Science. His research focuses on applying Natural Language Processing to automate the compliance checking process in the building industry. This application involves specialised domain terminology and knowledge, the structured and interlinked characteristics of legal texts, and the scarcity of labelled training data. His interest in generalisable machine learning models and learning from few examples can help to solve this domain application.

Supervisor: Michael Witbrock

Katharina Dost

Katharina Dost

PhD Student

Since July 2019 I am a PhD student in the School of Computer Science. Before, I was employed as a Data Scientist in marketing where my work centered around predictive models and clustering techniques. I did my undergraduate studies in Mathematics and my Master’s degree in Scientific Computer Science at the University of Mainz, Germany. My main research interests are Selection Bias identification and mitigation especially as a pre-processing step for a broad range of supervised or unsupervised models.

Supervisors: Pat Riddle and Joerg Wicker

Olivier Graffeuille

Olivier Graffeuille

PhD Student

I am working towards a PhD in Computer Science, after graduating from Engineering Science here at the University of Auckland. My current research is on using Machine Learning techniques to detect extreme climate events, namely using satellite data to detect cyanobacterial blooms in New Zealand lakes.

Supervisors: Moritz Lehmann, Yun Sing Koh, and Joerg Wicker

Zhenyun Deng

Zhenyun Deng

PhD Student

I am pursuing a PhD from the School of Computer Science at the University of Auckland. My research interests include Machine Learning and Natural Language Processing. My current research focuses on multi-step reasoning for complex question answering.

Supervisors: Michael Witbrock and Pat Riddle

Qiqi Wang

Qiqi Wang

PhD Student

I’m a PhD student from the School of Computer Science at the University of Auckland. I have an M.E from the University of Western Australia and received both B.E and LL.B. from Southwest University, China. My current research focuses on applying Artificial Intelligence in Law.

Supervisors: Kaiqi Zhao and Robert Amor

Aaron Keesing

Aaron Keesing

PhD Student

Aaron studied computer science and mathematics at undergraduate level before completing his BSc(Hons) dissertation on anomaly detection in wireless sensor networks. He then started his PhD research, currently supervised by Yun Sing Koh and Michael Witbrock. His research is focussed on improving the robustness of speech emotion recognition across diverse accents and languages. Aaron’s other interests more generally include affective computing, speech technology, artificial intelligence and mathematics.

Supervisors: Michael Witbrock and Yun Sing Koh

Alumni

Ming-Bin (Bryan) Chen

Ming-Bin (Bryan) Chen

MSc Student (2020-2021)

Coming from the multi-disciplines background of science and art, Ming-Bin’s primary research interests are in the intersection of computer science and linguistics, particularly AI in journalism. He is currently a research master student at the School of Computer Science of the University of Auckland, supervised by Professor Michael Witbrock. His current research project is developing an open domain interviewing agent, a dialogue bot capable of asking interviewing questions given a topic.

Supervisors: Michael Witbrock