I am currently looking for PhD, Honours, or Masters students, I typically accept two new PhD candidates per year. If you are interested in applying, check my research areas and contact me by mail with your CV attached. Please check the doctoral study information page for information on entry requirements and the application procedure.
If you are one of top students from a good university, there are the University of Auckland Doctoral Scholarship, other postgraduate scholarships and country-specific scholarships that you can apply for.
If you are a top student from China, check the China Scholarship Council (CSC) scholarship.
Finally, the New Zealand Government offers Scholarships to eligible citizens of various countries.
For German students or PostDocs, DAAD has a list of funding opportunities for New Zealand.
Callaghan Innovation offers student grants for PhD and masters research in collaboration with industry.
Students
PhD Students
- Mark Chen - Adversarial Attacks on Time Series (since May 2023, with Gill Dobbie)
- Ioannis Ziogas - Machine Learning Models for Rare Event Data: Applications, Limitations, and Performance (since February 2023, with Gill Dobbie)
- Cathy Hua - Query-Focused, Analysis-Friendly Text Summarisation of Survey Responses (since February 2022, with Katerina Taskova, Paul Denny, and Gill Dobbie)
- Michael Chen - Application of Multi-Agent Reinforcement Learning in the Penetration Testing for Small to Medium Business Networks (since March 2021, with Giovanni Russello)
- Xuan (Johnny) Zhu - A mathematical model guided machine learning method for understanding epidemic multiple wave mechanisms (since January 2021, with Gill Dobbie and Stephen MacDonell)
- Olivier Graffeuille - Machine Learning for Extreme Event Detection (since August 2020, with Yun Sing Koh and Moritz Lehmann)
- Annie Lu - Machine Learning in Longitudinal Studies for "Growing Up in New Zealand" (since May 2020, with Yun Sing Koh)
- Xinglong (Luke) Chang - Adversarial Learning (since October 2019, with Gill Dobbie)
- Katharina Dost - Defining Reliable Machine Learning using Adversarial Learning (since July 2019, with Pat Riddle)
- Jonathan Kim - Towards Robust Semantic Scene Understanding through Joint Optimisation of Visual SLAM and Deep Convolutional Neural Networks (since February 2019, with Pat Riddle)
- Nooriyan Poonawala-Lohani - Predictive Analytics for Early Warning of Influenza-like Illness (since February 2019, with Pat Riddle, Claire Newbern, Mehnaz Adnan)
MSc Students
- Marrick Lip - A Machine Learning Framework for the Analysis of Bat Calls (February 2022-February 2023, with Kaiqi Zhao)
- Andrew Chester - Detecting Bias in Machine Learning Algorithms: End to End De-identification Framework for Clinical Text (March 2020-April 2021, with Yun Sing Koh)
- Katharina Dost - Boolean Matrix Decomposition for Giant Matrices (March 2016-September 2016, with Stefan Kramer)
- Steffen Albrecht - Data Mining for The Cancer Genome Atlas (January 2016-July 2016, with Stefan Kramer)
- Christian Sußenberger - Predicting Toxicity of Biodegradation Products Using REST (May 2014-November 2014, with Stefan Kramer)
- Christoph Brosdau - Service Oriented Data Mining for Biological Data (January 2008-July 2008, with Stefan Kramer and Lothar Richter)
- Daniela Bieley - Integration of String Mining in an Inductive Database (January 2008-July 2008, with Stefan Kramer and Lothar Richter)
Honours Projects
- Sam Chen - Adversarial Attacks on Clustering Algorithms (since July 2022, with Gill Dobbie)
- Liam Brydon - Finding Patterns in Chemical Reactions (February 2022-November 2022, with Katharina Dost and Gill Dobbie)
- Maxwell Zhu - Machine Learning Matching Algorithms in Dating Platforms (February 2022-November 2022, with Jessica Maxwell and Katerina Taskova)
- Viaan Saunderson - Adversarial Attacks on Graphs (February 2022-November 2022, with Kaiqi Zhao)
- Zac Pullar-Strecker - enviPath (February 2022-November 2022, with Katharina Dost, Kathrin Fenner, and Gill Dobbie)
- Chong Chuah - Bias in Machine Learning (February 2022-November 2022, with Katharina Dost, Ioannis Ziogas, and Gill Dobbie)
- Mark Chen - Adversarial Learning for Time Series Data (July 2021-July 2022, with Gill Dobbie)
- Hamish Duncanson - IMITATE: Identification and Mitigation of Selection Bias (March 2021-June 2021, with Pat Riddle and Katharina Dost)
- Milan Law - Data Analysis of COVID-19 Data Sets (March 2020-November 2020, with Katerina Taskova, Gill Dobbie, and Thomas Lumley)
- Kitty Li - Mining the RDF Graph to Improve the Performance of Classifiers (March 2019-October 2019, with Pat Riddle)
Summer Scholarships
- Liam Brydon - Finding Patterns in Chemical Reactions (December 2021-February 2022, with Katharina Dost)
- Ryan La - Auditing Machine Learning Models: Quantifying Reliability using Adversarial Regions (December 2021-February 2022, with Katharina Dost)
- Sarah Kim - Identifying and analysing bat calls (December 2021-February 2022, with Katharina Dost)
- Yuye Zhang - Auditing Machine Learning Models: Quantifying Reliability using Adversarial Regions (December 2021-February 2022, with Katharina Dost)
- Hamish Duncanson - Image Compression with Multivariate Decision Trees (December 2020-February 2021, with Bernhard Pfahringer)
- Zac Pullar-Strecker - Adversarial Active Learning (December 2020-February 2021, with Katharina Dost)
- Chloe Haigh - Privacy Defense (December 2019-February 2020)
- Matthew Mulvey - Machine Learning in the Analysis of Mass Spectrometry Data (December 2019-February 2020, with Katerina Taskova)
- Cathy Hua - Advanced Methods for Boolean Matrix Decomposition (December 2018-February 2019, with Bernhard Pfahringer)
- Hasnain Cheena - The Smell of Fear (December 2018-February 2019)
- Rayner Rebello - Advanced Methods for Boolean Matrix Decomposition (December 2018-February 2019, with Bernhard Pfahringer)
Master of Professional Studies in Data Science
- Tsz Fung Ip - New Zealand Long-tailed Bat Audio Analysis with Machine Learning (July 2021-July 2022, with Katharina Dost)
- Xianzhong Li - Inference of Cluster Information (March 2021-June 2021, with Katharina Dost)
- Xiao Li - Prediction of Earthquakes in the Ring of Fire (March 2021-June 2021, with Jason Tam)
- Yuanchi Ma - Inference of Cluster Information (March 2021-June 2021, with Katharina Dost)
- Zhe Wu - Prediction of Earthquakes in the Ring of Fire (March 2021-June 2021, with Jason Tam)
- Bruno Naveen Joswa - Identififying and Analysing Bat Calls (July 2020-December 2020, with Yun Sing Koh)
- Mary Grace De la Pena - Machine Learning-based Prediction of Biodegradation Persistence (July 2020-November 2020, with Katerina Taskova)
- Josh Bensemann - Change Mining in the Smell of Fear Data Set (July 2019-July 2020, with David Huang)
- Owen Meyer - Analysis of the CARIBIC Data Set (July 2019-July 2020, with David Huang)
- Charles Tremlett - Generating Chemical Structures and Improving Models using Reinforcement Learning (February 2019-October 2019, with Pat Riddle)
- Catherine Liu - Dynamic Pricing (July 2018-June 2019)
- Loukas Lyden - Modelling User Behaviour in Online Shopping (July 2018-June 2019)
- Masoumeh Shariat - Analysis of Petrol related VOCs in the CARIBIC Data Set (July 2018-June 2019, with David Huang)
- Samantha Cen - Identifying Contrails in the CARIBIC Data Set (July 2018-June 2019)
- Ziqing Yan - A New Field of Data Mining: Classification of Movies based on VOCs (March 2018-June 2018)
Engineering Part 4 Projects
- Angela Hollings - Ear, nose and throat app development (March 2021-October 2021, with Gill Dobbie and Raymond Kim)
- Elizabeth Yap - Ear, nose and throat app development (March 2021-October 2021, with Gill Dobbie and Raymond Kim)
380 Projects
- Jonathan Leung - Model Response to Electroconvulsive Therapy Changes based on EEG Traces (July 2021-October 2021, with Katerina Taskova)
- Hasnain Cheena - Machine Learning Approaches for Mass Spectrometry Data Analysis (July 2020-November 2020, with Katerina Taskova)
- Cathy Hua - Machine Learning Analysis of Student Feedback (March 2020-June 2020)
- Chloe Haigh - Biodegradation Half-Life Prediction (March 2020-June 2020, with Katerina Taskova)
- Aryan Lobie - Weather Prediction using Deep Neural Networks (July 2019-October 2019, with Pat Riddle)
- Sichun (Victor) Yin - Advanced Boolean Matrix Decomposition (March 2018-June 2018)
- Tom Fevriér - Identifing Markers for Human Emotion in Breath Using Convolutional Autoencoders on Movie Data (March 2018-June 2019, with Pat Riddle)
Master of Information Technology Projects
- Dingguang Lyu - Business Analyst (December 2021-February 2022)
- Aditio Nugroho - Proof of Concept - Salesforce Utility Cloud (November 2020-February 2021)
- Hiu Wing Doris - Proof of Concept - Salesforce Utility Cloud (November 2020-February 2021)
- Shakeel Khan - Proof of Concept - Salesforce Utility Cloud (November 2020-February 2021)
- Shriya Sadhu - Proof of Concept - Salesforce Utility Cloud (November 2020-February 2021)
- Hongnan Dou - Crash Prediction (August 2020-October 2020)
- Jiangning Lin - Crash Prediction (August 2020-October 2020)
- Wenjie Xu - Crash Prediction (August 2020-October 2020)
- Xiangli (Ben) Cheng - Crash Prediction (August 2020-October 2020)
- Catherine Blandin De Chalain - Managed Service Customer Portal (August 2019-October 2019)
- Pradeep Kumar - Bitcoin Price Prediction (August 2018-October 2018)
- Xeshu Shen - CCTV Analytics Build (August 2018-October 2020)
- Ning Hua - Interpreting Ensemble of Decision Trees in Precision Medicine (January 2018-April 2018)
- Samil Farouqui - Acquire Online Data Analysis and Automation (January 2018-April 2018)