Dr Joerg Simon Wicker

Research | Current

My main research areas are machine learning and data mining, and its application to bioinformatcs, cheminformatics, computational sustainability, and privacy.

Areas of expertise

  • Machine Learning
  • Data Mining
  • Data Science
  • Cheminformatics
  • Computational Sustainability
  • Adversarial Learning
  • Bioinformatics
  • Privacy

Selected publications and creative works (Research Outputs)

  • Stönner C, Edtbauer, A., Derstroff, B., Bourtsoukidis, E., Klüpfel T, Wicker, J., & Williams, J. (2018). Proof of concept study: Testing human volatile organic compounds as tools for age classification of films. PloS one, 13 (10)10.1371/journal.pone.0203044
    URL: http://hdl.handle.net/2292/45814
  • Wicker, J., & Kramer, S. (2017). The best privacy defense is a good privacy offense: Obfuscating a search engine user's profile. Data Mining and Knowledge Discovery, 31 (5), 1419-1443. 10.1007/s10618-017-0524-z
  • Latino, D. A., Wicker, J., Gütlein M, Schmid, E., Kramer, S., & Fenner, K. (2017). Eawag-Soil in enviPath: A new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data. Environmental Science: Processes & Impacts, 19 (3), 449-464. 10.1039/c6em00697c
  • Williams, J., Stönner C, Wicker, J., Krauter, N., Derstroff, B., Bourtsoukidis, E., ... Kramer, S. (2016). Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath. Scientific Reports, 610.1038/srep25464
  • Wicker, J., Lorsbach, T., Gütlein M, Schmid, E., Latino, D., Kramer, S., & Fenner, K. (2016). enviPath--The environmental contaminant biotransformation pathway resource. Nucleic Acids Research, 44 (D1), D502-D508. 10.1093/nar/gkv1229
  • Wicker, J., Fenner, K., & Kramer, S. (2016). A hybrid machine learning and knowledge based approach to limit combinatorial explosion in biodegradation prediction. In J. Lassig, K. Kersting, K. Morik (Eds.) Computational Sustainability (pp. 75-97). Switzerland: SPRINGER-VERLAG BERLIN. 10.1007/978-3-319-31858-5_5
  • Wicker, J., Tyukin, A., & Kramer, S. (2016). A nonlinear label compression and transformation method for multi-label classification using autoencoders. In J. Bailey, L. Khan, T. Washio, G. Dobbie, J. Z. Huang, R. Wang (Eds.) Advances in Knowledge Discovery and Data Mining 20th Pacific-Asia Conference, PAKDD 2016, Proceedings, Part I, LNCS, volume 9651, 328-340. Auckland, New Zealand: SPRINGER-VERLAG BERLIN. 10.1007/978-3-319-31753-3_27
  • Wicker, J., Krauter, N., Derstorff, B., Stönner C, Bourtsoukidis, E., Klüpfel T, ... Kramer, S. (2015). Cinema data mining: The smell of fear. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1295-1304. Sydney, NSW, Australia. 10.1145/2783258.2783404


Contact details

Office hours

Mon 2pm-4pm

Primary office location

SCIENCE CENTRE 303 - Bldg 303
Level 5, Room 526
New Zealand

Web links