I am a lecturer at the Department of Computer Science at the University of Auckland and CTO of enviPath. My main research interests are Machine Learning and Data Mining and its applications in Bioinformatics, Cheminformatics, Computational Sustainability and Privacy.
I am currently looking for PhD, Honours, or Masters students, if you are interested in any of my research, contact me by mail.
Recent Publications
Journal Articles |
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Stönner, Christof; Edtbauer, Achim; Derstorff, Bettina; Bourtsoukidis, Efstratios; Klüpfel, Thomas; Wicker, Jörg; Williams, Jonathan Proof of concept study: Testing human volatile organic compounds as tools for age classification of films Journal Article PLOS One, 13 (10), pp. 1-14, 2018. Abstract | Links | BibTeX | Altmetric @article{Stonner2018, title = {Proof of concept study: Testing human volatile organic compounds as tools for age classification of films}, author = {Christof Stönner and Achim Edtbauer and Bettina Derstorff and Efstratios Bourtsoukidis and Thomas Klüpfel and Jörg Wicker and Jonathan Williams}, doi = {10.1371/journal.pone.0203044}, year = {2018}, date = {2018-10-11}, journal = {PLOS One}, volume = {13}, number = {10}, pages = {1-14}, publisher = {Public Library of Science}, abstract = {Humans emit numerous volatile organic compounds (VOCs) through breath and skin. The nature and rate of these emissions are affected by various factors including emotional state. Previous measurements of VOCs and CO2 in a cinema have shown that certain chemicals are reproducibly emitted by audiences reacting to events in a particular film. Using data from films with various age classifications, we have studied the relationship between the emission of multiple VOCs and CO2 and the age classifier (0, 6, 12, and 16) with a view to developing a new chemically based and objective film classification method. We apply a random forest model built with time independent features extracted from the time series of every measured compound, and test predictive capability on subsets of all data. It was found that most compounds were not able to predict all age classifiers reliably, likely reflecting the fact that current classification is based on perceived sensibilities to many factors (e.g. incidences of violence, sex, antisocial behaviour, drug use, and bad language) rather than the visceral biological responses expressed in the data. However, promising results were found for isoprene which reliably predicted 0, 6 and 12 age classifiers for a variety of film genres and audience age groups. Therefore, isoprene emission per person might in future be a valuable aid to national classification boards, or even offer an alternative, objective, metric for rating films based on the reactions of large groups of people.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Humans emit numerous volatile organic compounds (VOCs) through breath and skin. The nature and rate of these emissions are affected by various factors including emotional state. Previous measurements of VOCs and CO2 in a cinema have shown that certain chemicals are reproducibly emitted by audiences reacting to events in a particular film. Using data from films with various age classifications, we have studied the relationship between the emission of multiple VOCs and CO2 and the age classifier (0, 6, 12, and 16) with a view to developing a new chemically based and objective film classification method. We apply a random forest model built with time independent features extracted from the time series of every measured compound, and test predictive capability on subsets of all data. It was found that most compounds were not able to predict all age classifiers reliably, likely reflecting the fact that current classification is based on perceived sensibilities to many factors (e.g. incidences of violence, sex, antisocial behaviour, drug use, and bad language) rather than the visceral biological responses expressed in the data. However, promising results were found for isoprene which reliably predicted 0, 6 and 12 age classifiers for a variety of film genres and audience age groups. Therefore, isoprene emission per person might in future be a valuable aid to national classification boards, or even offer an alternative, objective, metric for rating films based on the reactions of large groups of people. | |
Wicker, Jörg; Kramer, Stefan The Best Privacy Defense is a Good Privacy Offense: Obfuscating a Search Engine User's Profile Journal Article Data Mining and Knowledge Discovery, 31 (5), pp. 1419-1443, 2017, ISSN: 1573-756X. Abstract | Links | BibTeX | Altmetric @article{wicker2017best, title = {The Best Privacy Defense is a Good Privacy Offense: Obfuscating a Search Engine User's Profile}, author = {Jörg Wicker and Stefan Kramer}, editor = {Kurt Driessens and Dragi Kocev and Marko Robnik-Šikonja and Myra Spiliopoulou}, url = {http://rdcu.be/tL0U}, doi = {10.1007/s10618-017-0524-z}, issn = {1573-756X}, year = {2017}, date = {2017-09-01}, journal = {Data Mining and Knowledge Discovery}, volume = {31}, number = {5}, pages = {1419-1443}, abstract = {User privacy on the internet is an important and unsolved problem. So far, no sufficient and comprehensive solution has been proposed that helps a user to protect his or her privacy while using the internet. Data are collected and assembled by numerous service providers. Solutions so far focused on the side of the service providers to store encrypted or transformed data that can be still used for analysis. This has a major flaw, as it relies on the service providers to do this. The user has no chance of actively protecting his or her privacy. In this work, we suggest a new approach, empowering the user to take advantage of the same tool the other side has, namely data mining to produce data which obfuscates the user’s profile. We apply this approach to search engine queries and use feedback of the search engines in terms of personalized advertisements in an algorithm similar to reinforcement learning to generate new queries potentially confusing the search engine. We evaluated the approach using a real-world data set. While evaluation is hard, we achieve results that indicate that it is possible to influence the user’s profile that the search engine generates. This shows that it is feasible to defend a user’s privacy from a new and more practical perspective.}, keywords = {}, pubstate = {published}, tppubtype = {article} } User privacy on the internet is an important and unsolved problem. So far, no sufficient and comprehensive solution has been proposed that helps a user to protect his or her privacy while using the internet. Data are collected and assembled by numerous service providers. Solutions so far focused on the side of the service providers to store encrypted or transformed data that can be still used for analysis. This has a major flaw, as it relies on the service providers to do this. The user has no chance of actively protecting his or her privacy. In this work, we suggest a new approach, empowering the user to take advantage of the same tool the other side has, namely data mining to produce data which obfuscates the user’s profile. We apply this approach to search engine queries and use feedback of the search engines in terms of personalized advertisements in an algorithm similar to reinforcement learning to generate new queries potentially confusing the search engine. We evaluated the approach using a real-world data set. While evaluation is hard, we achieve results that indicate that it is possible to influence the user’s profile that the search engine generates. This shows that it is feasible to defend a user’s privacy from a new and more practical perspective. | |
Latino, Diogo; Wicker, Jörg; Gütlein, Martin; Schmid, Emanuel; Kramer, Stefan; Fenner, Kathrin Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data Journal Article Environmental Science: Process & Impact, 2017. Abstract | Links | BibTeX | Altmetric @article{latino2017eawag, title = {Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data}, author = {Diogo Latino and Jörg Wicker and Martin Gütlein and Emanuel Schmid and Stefan Kramer and Kathrin Fenner}, doi = {10.1039/C6EM00697C}, year = {2017}, date = {2017-01-01}, journal = {Environmental Science: Process & Impact}, publisher = {The Royal Society of Chemistry}, abstract = {Developing models for the prediction of microbial biotransformation pathways and half-lives of trace organic contaminants in different environments requires as training data easily accessible and sufficiently large collections of respective biotransformation data that are annotated with metadata on study conditions. Here, we present the Eawag-Soil package, a public database that has been developed to contain all freely accessible regulatory data on pesticide degradation in laboratory soil simulation studies for pesticides registered in the EU (282 degradation pathways, 1535 reactions, 1619 compounds and 4716 biotransformation half-life values with corresponding metadata on study conditions). We provide a thorough description of this novel data resource, and discuss important features of the pesticide soil degradation data that are relevant for model development. Most notably, the variability of half-life values for individual compounds is large and only about one order of magnitude lower than the entire range of median half-life values spanned by all compounds, demonstrating the need to consider study conditions in the development of more accurate models for biotransformation prediction. We further show how the data can be used to find missing rules relevant for predicting soil biotransformation pathways. From this analysis, eight examples of reaction types were presented that should trigger the formulation of new biotransformation rules, e.g., Ar-OH methylation, or the extension of existing rules e.g., hydroxylation in aliphatic rings. The data were also used to exemplarily explore the dependence of half-lives of different amide pesticides on chemical class and experimental parameters. This analysis highlighted the value of considering initial transformation reactions for the development of meaningful quantitative-structure biotransformation relationships (QSBR), which is a novel opportunity of f ered by the simultaneous encoding of transformation reactions and corresponding half-lives in Eawag-Soil. Overall, Eawag-Soil provides an unprecedentedly rich collection of manually extracted and curated biotransformation data, which should be useful in a great variety of applications.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Developing models for the prediction of microbial biotransformation pathways and half-lives of trace organic contaminants in different environments requires as training data easily accessible and sufficiently large collections of respective biotransformation data that are annotated with metadata on study conditions. Here, we present the Eawag-Soil package, a public database that has been developed to contain all freely accessible regulatory data on pesticide degradation in laboratory soil simulation studies for pesticides registered in the EU (282 degradation pathways, 1535 reactions, 1619 compounds and 4716 biotransformation half-life values with corresponding metadata on study conditions). We provide a thorough description of this novel data resource, and discuss important features of the pesticide soil degradation data that are relevant for model development. Most notably, the variability of half-life values for individual compounds is large and only about one order of magnitude lower than the entire range of median half-life values spanned by all compounds, demonstrating the need to consider study conditions in the development of more accurate models for biotransformation prediction. We further show how the data can be used to find missing rules relevant for predicting soil biotransformation pathways. From this analysis, eight examples of reaction types were presented that should trigger the formulation of new biotransformation rules, e.g., Ar-OH methylation, or the extension of existing rules e.g., hydroxylation in aliphatic rings. The data were also used to exemplarily explore the dependence of half-lives of different amide pesticides on chemical class and experimental parameters. This analysis highlighted the value of considering initial transformation reactions for the development of meaningful quantitative-structure biotransformation relationships (QSBR), which is a novel opportunity of f ered by the simultaneous encoding of transformation reactions and corresponding half-lives in Eawag-Soil. Overall, Eawag-Soil provides an unprecedentedly rich collection of manually extracted and curated biotransformation data, which should be useful in a great variety of applications. | |
Inproceedings |
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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. @inproceedings{williams2019what, title = {What can we learn from the air chemistry of crowds?}, author = {Jonathan Williams and Christof Stönner and Achim Edtbauer and Bettina Derstorff and Efstratios Bourtsoukidis and Thomas Klüpfel and Nicolas Krauter and Jörg Wicker and Stefan Kramer}, editor = {Armin Hansel and Jürgen Dunkl}, url = {https://www.ionicon.com/sites/default/files/uploads/doc/Contributions_8th-PTR-MS-Conference-2019_web.pdf#page=122}, year = {2019}, date = {2019-05-10}, booktitle = {8th International Conference on Proton Transfer Reaction Mass Spectrometry and its Applications}, pages = {121-123}, publisher = {Innsbruck University Press}, address = {Innsbruck}, abstract = {Current PTR-MS technology allows hundreds of volatile trace gases in air to be measured every second at extremely low levels (parts per trillion). These instruments are often used in atmospheric research on planes and ships and even in the Amazon rainforest. Recently, we have used this technology to examine air composition changes caused by large groups of people (10,000-30,000) under real world conditions at a football match and in a movie theater. In both cases the trace gas signatures measured in ambient air are shown to reflect crowd behavior. By applying advanced data mining techniques we have shown that groups of people reproducibly respond to certain emotional stimuli (e.g. suspense and comedy) by exhaling specific trace gases. Furthermore, we explore whether this information can be used to determine the age classification of films.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Current PTR-MS technology allows hundreds of volatile trace gases in air to be measured every second at extremely low levels (parts per trillion). These instruments are often used in atmospheric research on planes and ships and even in the Amazon rainforest. Recently, we have used this technology to examine air composition changes caused by large groups of people (10,000-30,000) under real world conditions at a football match and in a movie theater. In both cases the trace gas signatures measured in ambient air are shown to reflect crowd behavior. By applying advanced data mining techniques we have shown that groups of people reproducibly respond to certain emotional stimuli (e.g. suspense and comedy) by exhaling specific trace gases. Furthermore, we explore whether this information can be used to determine the age classification of films. | |