About Karsten Steinhaeuser

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. He is actively involved in shaping an emerging research area called climate informatics, which lies at the intersection of computer science and climate sciences. 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 activities.

His research interests are broadly in 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. His work was recognized with the Best Poster Award at the 2009 SIAM Data Mining Doctoral Student Forum as well as being selected for presentation at the NSF-sponsored Doctoral Consortium held in conjunction with the 2010 International Conference on Computational Sustainability. At Notre Dame, he received the 2010 CRC Award for Computational Sciences and Visualization, and at ORNL he was honored with two Significant Event Awards, most recently for “Novel Analyses of the Simulation Results from the CCSM 3.0 Climate Model.”

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 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.

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