I'm working at the interface between machine learning and environmental science. My research currently focuses on the detection of extreme events in Earth observation data (such as fAPAR, NDVI, carbon fluxes). The question of how climate extremes affect ecosystems is of high importance for understanding climate-carbon feedbacks and hence future climate predictions. I try to identify large-scale extremes in impact variables and trace them back to climatic drivers and external disturbances.
I'm also part of the Department for Biogeochemical Integration at the MPI for Biogeochemistry in Jena.
| 2010- | PhD Student both at MPI for Intelligent Systems in Tuebingen and MPI for Biogeochemistry in Jena |
| 2010 | Diploma in Mathematics at Humboldt University of Berlin |
| 2009-2010 | Diploma Thesis at MPI for Biological Cybernetics in Tuebingen |
| 2003 | Abitur at Kreuzschule Dresden |
| 2013 | Visiting Researcher at the group of Anna Michalak at Carnegie Institution for Science, Department for Global Ecology, Stanford, CA, USA |
| 2009 | Internship at Potsdam Institute for Climate Impact Research (PIK) |
| 2007 | Internship at Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), Manaus, Brazil |
| 2003-2004 | Civilian Service (old people's home) |
| 2006-2010 | Scholar of the Evangelisches Studienwerk Villigst |
| 2010 | Coauthor of "Inferring Deterministic Causal Relations", winner of the Best Student Paper Award at UAI, 2010 |
| Classical Music, Singing, Football, Climate Change, Hiking |
Mooij, J., Peters, J., Janzing, D., Zscheischler, J., Schölkopf, B.
Distinguishing cause from effect using observational data: methods and benchmarks
Journal of Machine Learning Research, 17(32):1-102, 2016 (article)
Zscheischler, J.
A global analysis of extreme events and consequences for the terrestrial carbon cycle
Diss. No. 22043, ETH Zurich, Switzerland, ETH Zurich, Switzerland, 2014 (phdthesis)
Zscheischler, J., Michalak, A., Schwalm, M., Mahecha, M., Huntzinger, D., Reichstein, M., Berthier, G., Ciais, P., Cook, R., El-Masri, B., Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W., Wei, Y., Yang, J., Zeng, N.
Impact of Large-Scale Climate Extremes on Biospheric Carbon Fluxes: An Intercomparison Based on MsTMIP Data
Global Biogeochemical Cycles, 2014 (article)
Zscheischler, J., Reichstein, M., Harmeling, S., Rammig, A., Tomelleri, E., Mahecha, M.
Extreme events in gross primary production: a characterization across continents
Biogeosciences, 11, pages: 2909-2924, 2014 (article)
v Buttlar, J., Zscheischler, J., Mahecha, M.
An extended approach for spatiotemporal gapfilling: dealing with large and systematic gaps in geoscientific datasets
Nonlinear Processes in Geophysics, 21(1):203-215, 2014 (article)
Solly, E., Schöning, I., Boch, S., Kandeler, E., Marhan, S., Michalzik, B., Müller, J., Zscheischler, J., Trumbore, S., Schrumpf, M.
Factors controlling decomposition rates of fine root litter in temperate forests and grasslands
Plant and Soil, 2014 (article)
Zscheischler, J., Mahecha, M., v Buttlar, J., Harmeling, S., Jung, M., Rammig, A., Randerson, J., Schölkopf, B., Seneviratne, S., Tomelleri, E., Zaehle, S., Reichstein, M.
A few extreme events dominate global interannual variability in gross primary production
Environmental Research Letters, 9(3):035001, 2014 (article)
Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M., Seneviratne, S., Zscheischler, J., Beer, C., Buchmann, N., Frank, D., Papale, D., Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A., Wattenbach, M.
Climate Extremes and the Carbon Cycle
Nature, 500, pages: 287-295, 2013 (article)
Zscheischler, J., Mahecha, M., Harmeling, S., Reichstein, M.
Detection and attribution of large spatiotemporal extreme events in Earth observation data
Ecological Informatics, 15, pages: 66-73, 2013 (article)
Jung, M., Zscheischler, J.
A Guided Hybrid Genetic Algorithm for Feature Selection with Expensive Cost Functions
In Proceedings of the International Conference on Computational Science, 18, pages: 2337 - 2346, Procedia Computer Science, (Editors: Alexandrov, V and Lees, M and Krzhizhanovskaya, V and Dongarra, J and Sloot, PMA), Elsevier, Amsterdam, Netherlands, ICCS, 2013 (inproceedings)
Janzing, D., Mooij, J., Zhang, K., Lemeire, J., Zscheischler, J., Daniušis, P., Steudel, B., Schölkopf, B.
Information-geometric approach to inferring causal directions
Artificial Intelligence, 182-183, pages: 1-31, May 2012 (article)
Zscheischler, J., Mahecha, M., Harmeling, S.
Climate classifications: the value of unsupervised clustering
In Proceedings of the International Conference on Computational Science , 9, pages: 897-906, Procedia Computer Science, (Editors: H. Ali, Y. Shi, D. Khazanchi, M. Lees, G.D. van Albada, J. Dongarra, P.M.A. Sloot, J. Dongarra), Elsevier, Amsterdam, Netherlands, ICCS, June 2012 (inproceedings)
Zscheischler, J., Mahecha, M., von Buttlar, J., Harmeling, S., Jung, M., Randerson, J., Reichstein, M.
Significant global reduction of carbon uptake by water-cycle driven extreme vegetation anomalies
Nature Geoscience, 2012 (article) In revision
Zscheischler, J., Janzing, D., Zhang, K.
Testing whether linear equations are causal: A free probability theory approach
In pages: 839-847, (Editors: Cozman, F.G. , A. Pfeffer), AUAI Press, Corvallis, OR, USA, 27th Conference on Uncertainty in Artificial Intelligence (UAI), July 2011 (inproceedings)
Daniusis, P., Janzing, D., Mooij, J., Zscheischler, J., Steudel, B., Zhang, K., Schölkopf, B.
Inferring deterministic causal relations
In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, pages: 143-150, (Editors: P Grünwald and P Spirtes), AUAI Press, Corvallis, OR, USA, UAI, July 2010 (inproceedings)
Zscheischler, J.
Inferring High-Dimensional Causal Relations using Free Probability Theory
Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)
© 2017 Max-Planck-Gesellschaft - Imprint
