Deutsch Intern
    Data Science Chair

    Michael Steininger, M.Sc.

    Chair of Data Science (Informatik X)
    University of Würzburg
    Am Hubland
    97074 Würzburg

    Email:  steininger@informatik.uni-wuerzburg.de

    Phone: (+49 931)  31 - 89482

    Office: Room B108 (Computer Science Building M2)

    Projects and Research Interests

    I joined the DMIR group for my PhD studies after receiving my master's degree in Computer Science at the university of Würzburg in early 2018. As a member of the BigData@Geo project, I am working on climate and air pollution modeling using machine learning techniques.


    Summer Term 2020:

    Summer Term 2019:

    Winter Term 2018/19:

    Summer Term 2018:



    • Evaluating the multi-task... - Download
      Dulny, A., Steininger, M., Lautenschlager, F., Krause, A., Hotho, A. (2020) “Evaluating the multi-task learning approach for land use regression modelling of air pollution”, in International Conference On Frontiers Of Artificial Intelligence And Machine Learning, IASED.
    • Anomaly Detection in Beeh... - Download
      Davidson, P., Steininger, M., Lautenschlager, F., Kobs, K., Krause, A., Hotho, A. (2020) “Anomaly Detection in Beehives using Deep Recurrent Autoencoders”, in Proceedings Of The 9Th International Conference On Sensor Networks (Sensornets 2020), SCITEPRESS – Science and Technology Publications, Lda., 142-149.
    • Lautenschlager, F., Becker, M., Kobs, K., Steininger, M., Davidson, P., Krause, A., Hotho, A. (2020) “OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning”, Atmospheric Environment, 233, 117535, available: http://www.sciencedirect.com/science/article/pii/S1352231020302703.
    • MapLUR: Exploring a New P... - Download
      Steininger, M., Kobs, K., Zehe, A., Lautenschlager, F., Becker, M., Hotho, A. (2020) “MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images”, ACM Trans. Spatial Algorithms Syst., 6(3), available: https://doi.org/10.1145/3380973.
    • Kobs, K., Steininger, M., Zehe, A., Lautenschlager, F., Hotho, A. (2020) “SimLoss: Class Similarities in Cross Entropy”, available: http://arxiv.org/abs/2003.03182.


    • EveryAware Gears: A Tool ... - Download
      Lautenschlager, F., Becker, M., Steininger, M., Hotho, A. (2018) “EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data”, in Burghardt, D., Chen, S., Andrienko, G., Andrienko, N., Purves, R. and Diehl, A., eds., Proceedings Of Vgi Geovisual Analytics Workshop, Colocated With Bdva 2018, KOPS.