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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
92
Citations
43566
World Ranking
537
National Ranking
25

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Daniel A. Keim is a researcher affiliated with the University of Konstanz in Germany. Their work spans primarily the field of Computer Science, with a strong focus on specialized subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Statistical and Nonlinear Physics, and Ecological Modeling.

The key topics addressed in their research include:

  • Data Visualization and Analytics
  • Explainable Artificial Intelligence (XAI)
  • Time Series Analysis and Forecasting
  • Video Analysis and Summarization
  • Species Distribution and Climate Change
  • Complex Network Analysis Techniques
  • Stock Market Forecasting Methods

Their recent scholarly publications demonstrate engagement with immersive analytics, human-centered machine learning, and medical imaging analytics, among other areas. Notable papers include:

  • "Immersive Analytics with Abstract 3D Visualizations: A Survey" (2021, Computer Graphics Forum)
  • "A Survey of Human-Centered Evaluations in Human-Centered Machine Learning" (2021, Computer Graphics Forum)
  • "PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers" (2020, European Radiology Experimental)
  • "The Value of Immersive Visualization" (2021, IEEE Computer Graphics and Applications)
  • "Potential short-term earthquake forecasting by farm animal monitoring" (2020, Ethology)

Daniel A. Keim frequently collaborates with several researchers, including Mennatallah El-Assady, Udo Schlegel, Johannes Fuchs, Frederik L. Dennig, and Matthias Miller. Such collaborations contribute to the breadth of their scientific output.

The venues where their work is most often published reflect a focus on both theoretical and applied aspects of computer graphics, visualization, and computational methods. These top publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • Computer Graphics Forum
  • IEEE Computer Graphics and Applications
  • Computers & Graphics

In addition to journal and conference articles, Daniel A. Keim has contributed to the academic literature through book publications. One such example is "Mastering the Information Age Solving Problems with Visual Analytics" (2022), published by the University of Groningen.

Best Publications

  • Information visualization and visual data mining

    D.A. Keim

  • On the Surprising Behavior of Distance Metrics in High Dimensional Spaces

    Charu C. Aggarwal;Alexander Hinneburg;Daniel A. Keim

  • The X-tree: an index structure for high-dimensional data

    Stefan Berchtold;Daniel A. Keim;Hans-Peter Kriegel

  • An efficient approach to clustering in large multimedia databases with noise

    Alexander Hinneburg;Daniel A. Keim

  • Visual Analytics: Definition, Process, and Challenges

    Daniel Keim;Gennady Andrienko;Jean-Daniel Fekete;Carsten Görg

  • Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases

    Christian Böhm;Stefan Berchtold;Daniel A. Keim

  • Mastering the information age : solving problems with visual analytics

    Daniel Keim;Jörn Kohlhammer;Geoffrey Ellis;Florian Mansmann

  • Challenges in Visual Data Analysis

    D.A. Keim;F. Mansmann;J. Schneidewind;H. Ziegler

  • Interactive Data Visualization: Foundations, Techniques, and Applications

    Matthew Ward;Georges Grinstein;Daniel Keim

  • Visual Analytics: Scope and Challenges

    Daniel A. Keim;Florian Mansmann;Jörn Schneidewind;Jim Thomas

  • What Is the Nearest Neighbor in High Dimensional Spaces

    Alexander Hinneburg;Charu C. Aggarwal;Daniel A. Keim

  • Designing pixel-oriented visualization techniques: theory and applications

    D.A. Keim

  • On Knowledge Discovery and Data Mining

    Daniel A. Keim

  • Visualization techniques for mining large databases: a comparison

    D.A. Keim;H.-P. Kriegel

  • Geovisual analytics for spatial decision support: Setting the research agenda

    G. Andrienko;N. Andrienko;P. Jankowski;D. Keim

  • A cost model for nearest neighbor search in high-dimensional data space

    Stefan Berchtold;Christian Böhm;Daniel A. Keim;Hans-Peter Kriegel

  • Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering

    Alexander Hinneburg;Daniel A. Keim

  • Feature-based similarity search in 3D object databases

    Benjamin Bustos;Daniel A. Keim;Dietmar Saupe;Tobias Schreck

  • VisDB: database exploration using multidimensional visualization

    D.A. Keim;H.-P. Kriegel

  • Visual exploration of large data sets

    Daniel A. Keim

Frequent Co-Authors

Umeshwar Dayal
Umeshwar Dayal Hitachi (Japan)
Hans-Peter Kriegel
Hans-Peter Kriegel Ludwig-Maximilians-Universität München
Tobias Schreck
Tobias Schreck Graz University of Technology
Gennady Andrienko
Gennady Andrienko Fraunhofer Institute for Intelligent Analysis and Information Systems
Natalia Andrienko
Natalia Andrienko Fraunhofer Institute for Intelligent Analysis and Information Systems
Stephen C. North
Stephen C. North Infovisible
Stefan Wrobel
Stefan Wrobel University of Bonn
Dietmar Saupe
Dietmar Saupe University of Konstanz
Thomas Seidl
Thomas Seidl Ludwig-Maximilians-Universität München
Siegfried Scherer
Siegfried Scherer Technical University of Munich

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