Karsten Steinhaeuser

Karsten Steinhaeuser

Research Associate at the University of Minnesota
Department of Computer Science & Engineering

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News & Events

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Contact

e-mailemail address snail mailUniversity of Minnesota
webwww.umn.edu/~ksteinha/ 4-192 Keller Hall
200 Union St SE
Minneapolis, MN 55455

CV

Curriculum Vitae (PDF)

Research Interests

Data mining and machine learning, specifically the construction and analysis of graphs/networks; large-scale data analysis, including parallel and distributed algorithms; applications to climate and earth sciences, ecology, biology, sustainability, medicine/healthcare, and social networks.

Bio

Karsten Steinhaeuser is a Research Associate in the Department of Computer Science and Engineering at the University of Minnesota. His primary responsibilities currently include two major research efforts: an NSF Expeditions in Computing on Understanding Climate Change: A Data Driven Approach and the GOPHER project, which is an R&D partner in the Planetary Skin Institute.
His research interests are centered around data mining and machine learning, in particular the construction and analysis of complex networks, with applications in diverse domains including (but not limited to) climate, ecology, and social networks. He is actively involved in shaping an emerging research area called climate informatics, which lies at the intersection of computer science and climate sciences, and his interests are more generally in interdisciplinary research and scientific problems relating to climate change and sustainability. He co-organizes the IEEE ICDM Workshop on Knowledge Discovery from Climate Data and the International Workshop on Climate Informatics, among others, and is engaged in numerous other professional service and community building activities.
He earned his PhD in Computer Science and Engineering (co-advised by Prof. Nitesh Chawla and Prof. Auroop Ganguly) from the University of Notre Dame in May 2011, where he was a member of the Data, Inference, Analysis and Learning (DIAL) laboratory as well as the Interdisciplinary Center for Network Science and Applications (iCeNSA); he also spent three years of his PhD studies as a member of the Geographic Information Science and Technology Group at Oak Ridge National Laboratory. He previously received an MS in Computer Science and Engineering (2007) and a BS, Summa Cum Laude in Computer Science (2005), both from the University of Notre Dame.

Publications

Book Chapters

Claire Monteleoni, Gavin A. Schmidt, Francis Alexander, Alexandru Niculescu-Mizil, Karsten Steinhaeuser, Michael Tippett, Arindam Banerjee, M. Benno Blumenthal, Auroop R. Ganguly, Jason E. Smerdon, Marco Tedesco (2013). Climate Informatics. Computational Intelligent Data Analysis for Sustainable Development, T. Yu, N. Chawla, S. Simoff. (Eds.), Taylor & Francis, 81-126.
Keywords: climate informatics, machine learning, climate science, interdisciplinary research

K. Steinhaeuser and N. V. Chawla (2009). A Network-Based Approach to Understanding and Predicting Diseases. Social Computing and Behavioral Modeling, H. Liu, J.J. Salerno, M.J. Young (Eds.), Springer, 209-216.
Keywords: medical informatics, data mining, networks, disease prediction

K. Steinhaeuser and N. V. Chawla (2008). Community Detection in a Large Real-World Social Network. Social Computing, Behavioral Modeling, and Prediction, H. Liu, J.J. Salerno, M.J. Young (Eds.), Springer, 168-175.
Keywords: social network analysis, telecommunications data, community detection, node attributes

Refereed Journal Articles

A. R. Ganguly, E. Kodra, A. Banerjee, S. Boriah, S. Chatterjee, S. Chaterjee, A. Choudhary, D. Das, J. Faghmous, P. Ganguli, S. Ghosh, K. Hayhoe, C. Hays, W. Hendrix, Q. Fu, J. Kawale, D. Kumar, V. Kumar, S. Liess, R. Mawalagedara, V. Mithal, R. Oglesby, K. Salvi, P. K. Snyder, K. Steinhaeuser, D. Wang, and D. Wuebbles (2014). Toward enhanced understanding and prediction of climate extremes using physics-guided data mining techniques. Nonlinear Processes in Geophysics, 21, 777-795.
Keywords: climate modeling, data mining, climate extremes, big data

K. Steinhaeuser, A. A. Tsonis (2014). A Climate Model Intercomparison at the Dynamics Level. Climate Dynamics, 42, 1665-1670.
Keywords: climate networks, climate dynamics, model intercomparison

K. Steinhaeuser, A. R. Ganguly and Nitesh V. Chawla (2012). Multivariate and Multiscale Dependence in the Global Climate System Revealed Through Complex Networks. Climate Dynamics, 39, 889-895.
Keywords: complex networks, correlation, teleconnections, reanalysis data

E. Parish, E. Kodra, K. Steinhaeuser and A. R. Ganguly (2012). Estimating Future Global per capita Water Availability based on Changes in Climate and Population. Computers & Geosciences, 42, 79-86.
Keywords: climate change impacts, population growth, resource scarcity, water availability

K. Steinhaeuser, N. V. Chawla and A. R. Ganguly (2011). Complex Networks as a Unified Framework for Descriptive Analysis and Predictive Modeling in Climate Science. Statistical Analysis and Data Mining - Special Issue: Networks, 5(4), 497-511.
Keywords: complex networks, climate data, network analysis, community detection, multivariate predictive modeling

E. Kodra, K. Steinhaeuser, and A. R. Ganguly (2011). Persisting Cold Extremes Under 21st Century Warming Scenarios. Geophysical Research Letters, 38, L08705.
Keywords: climate change, extreme events, cold spells, model projections

K. Steinhaeuser, N. V. Chawla and A. R. Ganguly (2010). An Exploration of Climate Data Using Complex Networks. ACM SIGKDD Explorations, 12(1), 25-32.
Keywords: complex networks, climate data, community detection, spatio-temporal patterns

K. Steinhaeuser and N. V. Chawla (2010). Identifying and Evaluating Community Structure in Complex Networks. Pattern Recognition Letters, 31(5), 413-421.
Keywords: complex networks, community detection, random walks, scalability, evaluation metrics, modularity

A. R. Ganguly, K. Steinhaeuser, D. J. Erickson III, M. L. Branstetter, E. Parish, N. Singh, J. B. Drake and L. Buja (2009). Higher trends but larger uncertainty and geographic variability in 21st century temperature and heat waves. Proceedings of the National Academy of Sciences USA, 106(37), 15555-15559.
Keywords: climate change, extremes, uncertainty, regional analysis

Refereed Conference and Workshop Publications

J. Xu, T. L. Wickramarathne, N. V. Chawla, E. K. Grey, K. Steinhaeuser, R. P. Keller, J. M. Keller, J. M. Drake, and D. M. Lodge (2014). Improving Management of Aquatic Invasions by Integrating Shipping Network, Ecological, and Environmental Data: Data Mining for Social Good. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), New York, NY.
Keywords: global shipping network, invasive species, biodiversity

V. Mithal, A. Khandelwal, S. Boriah, K. Steinhaeuser, V. Kumar (2013). Change Detection from Temporal Sequences of Class Labels: Application to Land Cover Change Mapping. SIAM International Conference on Data Mining (SDM), Austin, TX.
Keywords: time series analysis, change detection, remote sensing, land cover change

X. Chen, K. Steinhaeuser, S. Boriah, S. Chatterjee, V. Kumar (2013). Contextual Time Series Change Detection. SIAM International Conference on Data Mining (SDM), Austin, TX.
Keywords: time series analysis, change detection, contextual change

A. Karpatne, M. Blank, M. Lau, S. Boriah, K. Steinhaeuser, M. Steinbach, V. Kumar (2012). Importance of Vegetation Type in Forest Cover Estimation. Conference on Intelligent Data Understanding (CIDU), Boulder, CO.
Keywords: remote sensing, land cover, forest cover estimation

V. Mithal, Z. O'Connor, K. Steinhaeuser, S. Bortiah, V. Kumar, C. Potter, S. Klooster (2012). Time Series Change Detection using Segmentation: A Case Study for Land Cover Monitoring. Conference on Intelligent Data Understanding (CIDU), Boulder, CO.
Keywords: time series analysis, segmentation, remote sensing, land cover change

X. Chen, A. Karpatne, Y. Chamber, V. Mithal, M. Lau, K. Steinhaeuser, S. Boriah, M. Steinbach, V. Kumar, C. Potter, S. Klooster, T. Abraham, J.D. Stanley (2012). A New Data Mining Framework for Forest Fire Mapping. Conference on Intelligent Data Understanding (CIDU), Boulder, CO.    † Equal Contribution
Keywords: remote sensing, land cover change, forest fire mapping, time series analysis, change detection

J. Kawale, S. Chatterjee, D. Ormsby, K. Steinhaeuser, S. Liess, V. Kumar (2012). Testing the Significance of Spatio-temporal Teleconnection Patterns. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Beijing, China.
Keywords: spatio-temporal data mining, teleconnections, climate data, dipoles, significance testing

S. Chatterjee*, K. Steinhaeuser, A. Banerjee, S. Chatterjee, and A. R. Ganguly (2012). Spare Group Lasso: Consistency and Climate Applications. SIAM International Conference on Data Mining (SDM), Anaheim, CA.    * Best Student Paper
Keywords: sparse regression, group lasso, climate data, multivariate predictive modeling

K. Steinhaeuser, N. V. Chawla and A. R. Ganguly (2011). Comparing Predictive Power in Climate Data: Clustering Matters. International Symposium on Spatial and Temporal Databases (SSTD), Minneapolis, MN.
Keywords: complex networks, climate data, clustering methods, information content

A. Pelan, K. Steinhaeuser, N. V. Chawla, D. A. de Alwis Pitts and A. R. Ganguly (2011). Empirical Comparison of Correlation Measures and Pruning Levels in Complex Networks Representing the Global Climate System. IEEE Symposium Series on Computational Intelligence and Data Mining (CIDM), Paris, France.
Keywords: complex networks, climate data, correlation measures, network properties

K. Steinhaeuser, N. V. Chawla and A. R. Ganguly (2010). Complex Networks in Climate Science: Progress, Opportunities and Challenges. NASA Conference on Intelligent Data Understanding (CIDU), Mountain View, CA.
Keywords: complex networks, climate data, network properties, community detection, open questions

S.-C. Kao, A. R. Ganguly, K. Steinhaeuser (2009). Motivating Complex Dependence Structures in Data Mining: A Case Study with Anomaly Detection in Climate. IEEE ICDM Workshop on Knowledge Discovery from Climate Data (ClimateKD), Miami, FL.
Keywords: multivariate dependence, copulas, climate data, anomaly detection

K. Steinhaeuser, N. V. Chawla and A. R. Ganguly (2009). An Exploration of Climate Data Using Complex Networks. ACM SIGKDD Workshop on Knowledge Discovery from Sensor Data (SensorKDD), Paris, France.
Keywords: complex networks, climate data, community detection, spatio-temporal patterns

K. Steinhaeuser, N. V. Chawla and A. R. Ganguly (2009). Discovery of Climate Patterns with Complex Networks. International Conference on Network Science (NetSci), Venice, Italy.
Keywords: complex networks, climate data, community detection, spatial clusters

C. Moretti, K. Steinhaeuser, D. Thain and N. V. Chawla (2008). Scaling Up Classifiers to Cloud Computers. IEEE International Conference on Data Mining (ICDM), Pisa, Italy.    † Equal Contribution
Keywords: distributed data mining, cloud computing, large datasets, scalability analysis

A. R. Ganguly and K. Steinhaeuser (2008). Data Mining for Climate Change and Impacts. IEEE ICDM Workshop on Spatial and Spatio-Temporal Data Mining (SSTDM), Pisa, Italy.
Keywords: applied data mining, climate science, challenges, open questions

K. Steinhaeuser and N. V. Chawla (2008). Is Modularity the Answer to Evaluating Community Structure in Networks? International Conference on Network Science (NetSci), Norwich, UK.
Keywords: complex networks, community detection, evaluation metrics, modularity, rand index

K. Steinhaeuser and N. V. Chawla (2008). Scalable Learning with Thread-Level Parallelism. Midwest Artificial Intelligence and Cognitive Science Conference (MAICS), Cincinnati, OH.
Keywords: high-performance data mining, large datasets, scalability analysis, cray mta-2

K. Steinhaeuser, N. V. Chawla and P. M. Kogge (2006). Exploiting Thread-Level Parallelism to Build Decision Trees. ECML/PKDD Workshop on Parallel Data Mining (PDM), Berlin, Germany.
Keywords: high-performance data mining, large datasets, cray mta-2

K. Steinhaeuser, N. V. Chawla and C. Poellabauer (2006). Towards Learning-Based Sensor Management. ACM SIGMETRICS First Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SYSML), Saint-Malo, France.
Keywords: sensor networks, routing, node management

E. Parish, A. R. Ganguly and K. Steinhaeuser (2008). Climate Change in the Dominican Republic. Oak Ridge National Laboratory Technical Report Manual ORNL/TM-2008/168, Oak Ridge, TN.
Keywords: climate change, model projections, temperature, precipitation, sea level rise


Last modified: June 25, 2014

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