Intern
    Data Science Chair

    Machine Learning for Ecosystems and Climate Modeling

    In the past few years, applying data science and machine learning to ecosystems, environmental & climate data has become a central research area at our chair. We have successfully developed deep learning methods for improving climate models in the BigData@Geo project as well as the follow up project BigData@Geo 2.0 as well as machine learning-based air pollution models in the EveryAware and p2Map project. We’re also analyzing data from smart beehives to understand bee behavior and detect anomalies as swarming events in the we4Bee and BeeConnected projects.

     

    Projects

    BigData@Geo Logo

    BigData@Geo 2.0

    Developing machine learning based approaches for regional environmental prediction models.

    BigData@Geo Logo

    BigData@Geo

    Developing machine learning based approaches for regional environmental prediction models.

    BeeConnected

    Learning and researching on smart beehive data.

    we4bee

    Learning and researching on smart beehive data.

    Concluded Projects

    • EveryAware - A project for collaborative collection of environmental sensor data with low cost sensors.

    • p2Map - Learning understandable maps of air pollution leveraging a combination of low-cost mobile sensors.

    Publications

    • ConvMOS: climate model ou...
      ConvMOS: climate model output statistics with deep learning. Steininger, Michael; Abel, Daniel; Ziegler, Katrin; Krause, Anna; Paeth, Heiko; Hotho, Andreas. In Data Mining and Knowledge Discovery, 37(1), pp. 136–166. 2023.
    • DynaBench: A Benchmark Da...
      DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data. Dulny, Andrzej; Hotho, Andreas; Krause, Anna. In Machine Learning and Knowledge Discovery in Databases: Research Track, D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis, F. Bonchi (eds.), pp. 438–455. Springer Nature Switzerland, Cham, 2023.
    • Swarming Detection in Sma...
      Swarming Detection in Smart Beehives Using Auto Encoders for Audio Data. Janetzky, Pascal; Schaller, Melanie; Krause, Anna; Hotho, Andreas. In 2023 30th International Conference on Systems, Signals and Image Processing (IWSSIP), pp. 1–5. 2023.
    • Automatic Speech Detectio...
      Automatic Speech Detection on a Smart Beehive’s Raspberry Pi. Janetzky, Pascal; Lissmann, Philipp; Hotho, Andreas; Krause, Anna. In LWDA 2023 - Learning, Knowledge, Data, and Analysis. 2023.
    • ConvMOS: Climate Model Ou...
      ConvMOS: Climate Model Output Statistics with Deep Learning. Steininger, Michael; Abel, Daniel; Ziegler, Katrin; Krause, Anna; Paeth, Heiko; Hotho, Andreas. In Data Mining and Knowledge Discovery, P. Cellier; K. Dembczynski; A. Zimmermann; E. Devijver (eds.). Springer, 2022.
    • A sensor-driven approach for analyzing a beehive’s state. Davidson, Padraig; Hotho, Andreas; Krause, Anna. 2022.
    • Evaluating the multi-task...
      Evaluating the multi-task learning approach for land use regression modelling of air pollution. Dulny, Andrzej; Steininger, Michael; Lautenschlager, Florian; Krause, Anna; Hotho, Andreas. In Journal of Physics: Conference Series, 1834(1), p. 012004. {IOP} Publishing, 2021.
    • Anomaly Detection in Beeh...
      Anomaly Detection in Beehives: An Algorithm Comparison. Davidson, Padraig; Steininger, Michael; Lautenschlager, Florian; Krause, Anna; Hotho, Andreas. In International Conference on Sensor Networks, Vol. 1674 of Communications in Computer and Information Science, A. Ahrens, R. Prasad, C. Benavente-Peces, N. Ansari (eds.), pp. 1–20. Springer, 2021.
    • NeuralPDE: Modelling Dynamical Systems from Data. Dulny, Andrzej; Hotho, Andreas; Krause, Anna. 2021.
    • Detecting Presence Of Spe...
      Detecting Presence Of Speech In Acoustic Data Obtained From Beehives. Janetzky, Pascal; Davidson, Padraig; Steininger, Michael; Krause, Anna; Hotho, Andreas. In DCASE Workshop. 2021.
    • Semi-Supervised Learning ...
      Semi-Supervised Learning for Grain Size Distribution Interpolation. Kobs, Konstantin; Schäfer, Christian; Steininger, Michael; Krause, Anna; Baumhauer, Roland; Paeth, Heiko; Hotho, Andreas. In Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10--15, 2021, Proceedings, Part VI, pp. 34–44. Springer International Publishing, 2021.
    • Density-based weighting f...
      Density-based weighting for imbalanced regression. Steininger, Michael; Kobs, Konstantin; Davidson, Padraig; Krause, Anna; Hotho, Andreas. In Machine Learning, A. Appice; S. Escalera; J. A. Gamez; H. Trautmann (eds.). 2021.
    • OpenLUR: Off-the-shelf ai...
      OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning. Lautenschlager, Florian; Becker, Martin; Kobs, Konstantin; Steininger, Michael; Davidson, Padraig; Krause, Anna; Hotho, Andreas. In Atmospheric Environment, 233, p. 117535. 2020.
    • MapLUR: Exploring a New P...
      MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images. Steininger, Michael; Kobs, Konstantin; Zehe, Albin; Lautenschlager, Florian; Becker, Martin; Hotho, Andreas. In ACM Trans. Spatial Algorithms Syst., 6(3). Association for Computing Machinery, New York, NY, USA, 2020.
    • Evaluating the multi-task...
      Evaluating the multi-task learning approach for land use regression modelling of air pollution. Dulny, Andrzej; Steininger, Michael; Lautenschlager, Florian; Krause, Anna; Hotho, Andreas. In International Conference on Frontiers of Artificial Intelligence and Machine Learning. IASED, 2020.
    • Deep Learning for Climate...
      Deep Learning for Climate Model Output Statistics. Steininger, Michael; Abel, Daniel; Ziegler, Katrin; Krause, Anna; Paeth, Heiko; Hotho, Andreas. In Tackling Climate Change with Machine Learning Workshop at NeurIPS 2020. 2020.
    • Anomaly Detection in Beeh...
      Anomaly Detection in Beehives using Deep Recurrent Autoencoders. Davidson, Padraig; Steininger, Michael; Lautenschlager, Florian; Kobs, Konstantin; Krause, Anna; Hotho, Andreas. In Proceedings of the 9th International Conference on Sensor Networks (SENSORNETS 2020), pp. 142–149. SCITEPRESS – Science and Technology Publications, Lda., 2020.
    • EveryAware Gears: A Tool ...
      EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data. Lautenschlager, Florian; Becker, Martin; Steininger, Michael; Hotho, Andreas. In Proceedings of VGI Geovisual Analytics Workshop, colocated with BDVA 2018, D. Burghardt, S. Chen, G. Andrienko, N. Andrienko, R. Purves, A. Diehl (eds.). KOPS, 2018.
    • Adaptive kNN Using Expect...
      Adaptive kNN Using Expected Accuracy for Classification of Geo-spatial Data. Kibanov, Mark; Becker, Martin; Müller, Juergen; Atzmüller, Martin; Hotho, Andreas; Stumme, Gerd. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing, of SAC ’18, pp. 857–865. ACM, Pau, France, 2018.
    • Air Trails -- Urban Air Q...
      Air Trails -- Urban Air Quality Campaign Exploration Patterns. Becker, Martin; Lautenschlager, Florian; Hotho, Andreas. 2018.
    • Participatory sensing, op...
      Participatory sensing, opinions and collective awareness. Loreto, Vittorio; Haklay, Mordechai; Hotho, Andreas; Servedio, Vito C. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca. Springer, 2017.
    • Experimental Assessment o...
      Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson. Gravino, Pietro; S{\^\i}rbu, Alina; Becker, Martin; Servedio, Vito DP; Loreto, Vittorio. In Participatory Sensing, Opinions and Collective Awareness, pp. 337–362. Springer, 2017.
    • Collective Sensing Platfo...
      Collective Sensing Platforms. Atzmueller, Martin; Becker, Martin; Mueller, Juergen. In Participatory Sensing, Opinions and Collective Awareness, pp. 115–133. Springer, 2017.
    • Applications for Environm...
      Applications for Environmental Sensing in EveryAware. Atzmueller, Martin; Becker, Martin; Molino, Andrea; Mueller, Juergen; Peters, Jan; S{\^\i}rbu, Alina. In Participatory Sensing, Opinions and Collective Awareness, pp. 135–155. Springer, 2017.
    • Participatory Patterns in...
      Participatory Patterns in an International Air Quality Monitoring Initiative. Sîrbu, Alina; Becker, Martin; Caminiti, Saverio; De Baets, Bernard; Elen, Bart; Francis, Louise; Gravino, Pietro; Hotho, Andreas; Ingarra, Stefano; Loreto, Vittorio; Molino, Andrea; Mueller, Juergen; Peters, Jan; Ricchiuti, Ferdinando; Saracino, Fabio; Servedio, Vito D. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca; Van den Bossche, Joris. In PLoS ONE, 10(8), p. e0136763. Public Library of Science, 2015.
    • Subjective vs. Objective Data: Bridging the Gap. Becker, Martin; Hotho, Andreas; Mueller, Juergen; Kibanov, Mark; Atzmueller, Martin; Stumme, Gerd. 2014.
    • Awareness and Learning in...
      Awareness and Learning in Participatory Noise Sensing. Becker, Martin; Caminiti, Saverio; Fiorella, Donato; Francis, Louise; Gravino, Pietro; Haklay, Mordechai (Muki); Hotho, Andreas; Loreto, Vittorio; Mueller, Juergen; Ricchiuti, Ferdinando; Servedio, Vito D. P.; Sîrbu, Alina; Tria, Francesca. In PLoS ONE, 8(12), p. e81638. Public Library of Science, 2013.
    • Tag Recommendations for S...
      Tag Recommendations for SensorFolkSonomies. Mueller, Juergen; Doerfel, Stephan; Becker, Martin; Hotho, Andreas; Stumme, Gerd. In Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings, Vol. 1066. CEUR-WS, Aachen, Germany, 2013.
    • A Generic Platform for Ub...
      A Generic Platform for Ubiquitous and Subjective Data. Becker, Martin; Mueller, Juergen; Hotho, Andreas; Stumme, Gerd. In 1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings, p. New York, NY, USA. ACM, 2013.
    • Modeling and Mining Ubiquitous Social Media. Atzmueller, Martin; Chin, Alvin; Helic, Denis; Hotho, Andreas. In Vol. 7472 of Lecture Notes in Computer Science. Springer Verlag, Heidelberg, Germany, 2012.
    • {Generic Pattern Trees fo...
      {Generic Pattern Trees for Exhaustive Exceptional Model Mining}. Lemmerich, Florian; Becker, Martin; Atzmueller, Martin. In Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Springer Verlag, Heidelberg, Germany, 2012.
    • Ubicon: Observing Social ...
      Ubicon: Observing Social and Physical Activities. Atzmueller, Martin; Becker, Martin; Doerfel, Stephan; Kibanov, Mark; Hotho, Andreas; Macek, Björn-Elmar; Mitzlaff, Folke; Mueller, Juergen; Scholz, Christoph; Stumme, Gerd. In IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012. IEEE, Washington, DC, USA, 2012.