Dr. Mike Sips

Mike Sips
Dr. Mike Sips
Group Leader
Telegrafenberg
Building A 20, Room 303
14473 Potsdam
+49 331 288-1982
+49 331 288-1163
mike.sips@gfz-potsdam.de

Function and Responsibilities:

Research Interests:

I am cooperating with a fantastic set of colleagues pursuing research on many diverse projects in big data analytics and explainable AI. We develop approaches that support data scientists' essential steps: a) recognize data, b) understand data, c) exploit data, and d) explain results. We support each step in our approaches through novel algorithms for analyzing and displaying data. We develop our approaches in close collaboration with scientists and users. Our flagship projects are GeoMultiSens and SEVA. Here is a high-level sampling:

  • Interactive Visual Approach to support building surrogate models with Janis Jatnieks.
  • Explainable Artificial Intelligence with Marie Schaefer.
  • Sustainable Research and Development Approach for Visual Analytics Approaches with Johann-Christoph Freytag.
  • Artificial Intelligence for Flood monitoring with Mahdi Motagh.
 
Recent Talks: 
  • SEVA: Visual Analytics for Scalable Change Detection. German Society for Photogrammetry, Remote Sensing and Geoinformation. March 2020, Stuttgart.
  • SEVA - Scalable Change Detection. DLR Symposium Neue Perspektiven der Erdbeobachtung. November 2019, Köln.
  • BigData-Analytics @ GFZ. Martin-Luther-Universität Halle-Wittenberg. Juni 2019, Halle/Saale.
  • Wie Unternehmen von Geofernerkundungsdaten profitieren können. - IHK Berlin and Bitkom Big Data Summit Berlin (together with Andre Hollstein), Berlin, September 2016 [Talk-Hollstein] [Talk-Sips]
  • GeoMultiSens - Scalable Multisensoral Analysis of Satellite Remote Sensing Data. - ESA Open Science 2016, ESA-ESRIN, Frascati (Rom), Italy, September 2016
  • Fast Recurrence Quantification Analysis and its Potential for Visual Analytics. - Perspectives in Non-Linear Dynamics (PNLD 2016), Humboldt-Universität zu Berlin, July 2016
  • Toward a Scientific Method for the Development of Visual Analytics Approaches. - Computer Science Colloquium, Friedrich-Schiller-Universität Jena, July 2016
  • Toward a Scientific Method for the Development of Visual Analytics Approaches. - Universität Leipzig, July 2016
  • Scalable Analysis of Big Remote Sensing Data. - VDI - Arbeitskreis Mess- und Automatisierungstechnik, Universität Kassel, June 2016. [Talk]
 
 

Recent Publications:

  • Sips, M., Köthur, P. & Eggert, D.: Toward a Visual Analytics Approach to Support Multi-Sensor Analysis in Remote Sensing Science. Datenbank Spektrum (2016) 16(3): 219--225 doi:10.1007/s13222-016-0232-7 [Article]
  • Tobias Rawald and Mike Sips and Norbert Marwan:PyRQA - Conducting Recurrence Quantification Analysis on Very Long Time Series Efficiently. Computers & GeoScience. doi: 10.1016/j.cageo.2016.11.016 [Artikel]

Current Activities:

  • Research Visit at DLR Institut Data Science und Lehrstuhl für Theoretische Informatik II, Friedrich-Schiller-Universität Jena, Oktober 2020, Jena
  • Invited Speaker of German contingent to the Transatlantic Dialog "Big Data and Cybersecurity", Februrary 2018, Ottawa (Canada).
  • Lecture "Visual Analytics for spatio-temporal data", Humboldt-Universität zu Berlin, WS 2017/2018
  • Visual Analytics and Maschine Learning, Research Visit of the Lehrstuhl für Theoretische Informatik II, Friedrich-Schiller-Universität Jena, November 2016

 

Career:

  • 2010-present: Scientific leader (tenured) of the research group "Big Data Analytics"

Education:

  • Master (2001 Martin-Luther-Universität Halle) und PhD (2005 Universität Konstanz) in computer science. 
  • Stanford University (2006-2008) and Max-Planck-Institut Informatik (2008-2010)

Projects:

Publications