I am senior lecturer at the School of Computer Science of the University of Auckland and CTO of enviPath. I am member of the Machine Learning Group at UoA. My main research area is machine learning and its application to bioinformatics, cheminformatics, computational sustainability, and privacy. My approach to research is to use interesting and challenging questions in other research areas and develop new machine learning methods that address them to potentially advance not only the field of machine learning, but also the area it is applied to. In my career, I worked on diverse machine learning topics including autoencoders, Boolean matrix decomposition, inductive databases, multi-label classification, privacy-preserving data mining, adversarial learning, and time series analysis.

I am currently looking for PhD, Honours, or Masters students, if you are interested in any of my research areas, contact me by mail.

Recent Publications

Journal Articles

Roeslin, Samuel; Ma, Quincy; Juárez-Garcia, Hugon; Gómez-Bernal, Alonso; Wicker, Jörg; Wotherspoon, Liam

A machine learning damage prediction model for the 2017 Puebla-Morelos, Mexico, earthquake Journal Article

Earthquake Spectra, 2020.

Abstract | Links | BibTeX | Altmetric

Jonauskaite, Domicele; Wicker, Jörg; Mohr, Chrisine; Dael, Nele; Havelka, Jelena; Papadatou-Pastou, Marietta; Zhang, Meng; Oberfeld, Daniel

A machine learning approach to quantifying the specificity of color-emotion associations and their cultural differences Journal Article

Royal Society Open Science, 6 (9), pp. 190741, 2019.

Abstract | Links | BibTeX | Altmetric


Chester, Andrew; Koh, Yun Sing; Sun, Quan; Wicker, Jörg; Lee, Junjae

Balancing Utility and Fairness against Privacy in Medical Data Inproceedings Forthcoming

IEEE Symposium Series on Computational Intelligence, IEEE, Forthcoming.

Abstract | BibTeX

Dost, Katharina; Taskova, Katerina; Riddle, Pat; Wicker, Jörg

Your Best Guess When You Know Nothing: Identification and Mitigation of Selection Bias Inproceedings Forthcoming

2020 IEEE International Conference on Data Mining (ICDM), IEEE, Forthcoming.

Abstract | BibTeX

Roeslin, Samuel; Ma, Quincy; and Chigullapally, Pavan; Wicker, Jörg; Wotherspoon, Liam

Feature Engineering for a Seismic Loss Prediction Model using Machine Learning, Christchurch Experience Inproceedings Forthcoming

17th World Conference on Earthquake Engineering, Forthcoming.

Abstract | BibTeX

Roeslin, Samuel; Ma, Quincy; Wicker, Jörg; Wotherspoon, Liam

Data integration for the development of a seismic loss prediction model for residential buildings in New Zealand Inproceedings

Cellier, Peggy; Driessens, Kurt (Ed.): Machine Learning and Knowledge Discovery in Databases, pp. 88-100, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-43887-6.

Abstract | Links | BibTeX | Altmetric

Wicker, Jörg; Hua, Yan Cathy; Rebello, Rayner; Pfahringer, Bernhard

XOR-based Boolean Matrix Decomposition Inproceedings

Wang, Jianyong; Shim, Kyuseok; Wu, Xindong (Ed.): 2019 IEEE International Conference on Data Mining (ICDM), pp. 638-647, IEEE, 2019, ISBN: 978-1-7281-4604-1.

Abstract | Links | BibTeX | Altmetric

Williams, Jonathan; Stönner, Christof; Edtbauer, Achim; Derstorff, Bettina; Bourtsoukidis, Efstratios; Klüpfel, Thomas; Krauter, Nicolas; Wicker, Jörg; Kramer, Stefan

What can we learn from the air chemistry of crowds? Inproceedings

Hansel, Armin; Dunkl, Jürgen (Ed.): 8th International Conference on Proton Transfer Reaction Mass Spectrometry and its Applications, pp. 121-123, Innsbruck University Press, Innsbruck, 2019.

Abstract | Links | BibTeX