This image shows David Hägele

David Hägele

M. Sc.

Wiss. Mitarbeiter
Visualisierungsinstitut der Universität Stuttgart (VISUS)
Arbeitsgruppe Weiskopf

Contact

+49 711 685 88625

Allmandring 19
70569 Stuttgart
Deutschland
Room: 00.010

  1. 2025

    1. T. Krake, D. Klötzl, D. Hägele, and D. Weiskopf, “Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess,” IEEE Transactions on Visualization and Computer Graphics, Feb. 2025, doi: 10.1109/TVCG.2024.3364388.

  2. 2024

    1. D. Hägele, Y. Tang, and D. Weiskopf, “Visual Compositional Data Analytics for Spatial Transcriptomics,” IEEE VIS Workshop on Bio+Med+Vis. arXiv, 2024. doi: 10.48550/ARXIV.2409.07306.
    2. D. Saupe, K. Rusek, D. Hägele, D. Weiskopf, and L. Janowski, “Maximum Entropy and Quantized Metric Models for Absolute Category Ratings,” IEEE Signal Processing Letters, 2024, doi: 10.1109/LSP.2024.3480832.
    3. L. Reichmann, D. Hägele, and D. Weiskopf, “Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions,” in 2024 IEEE 14th Symposium on Large Data Analysis and Visualization (LDAV), 2024, pp. 43–53. doi: 10.1109/LDAV64567.2024.00008.
    4. M. Evers, D. Hägele, S. Döring, and D. Weiskopf, “Progressive Glimmer: Expanding Dimensionality in Multidimensional Scaling,” IEEE VIS Workshop on Progressive Data Analysis and Visualization. arXiv, 2024. doi: 10.48550/ARXIV.2410.19430.
    5. P. Paetzold, D. Hägele, M. Evers, D. Weiskopf, and O. Deussen, “UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox,” IEEE VIS Workshop on Uncertainty Visualization: Applications, Techniques, Software, and Decision Frameworks. arXiv, 2024. doi: 10.48550/ARXIV.2409.10217.

  3. 2022

    1. D. Hägele, T. Krake, and D. Weiskopf, “Uncertainty-Aware Multidimensional Scaling,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–10, 2022, doi: 10.1109/tvcg.2022.3209420.
    2. D. Hägele et al., “Uncertainty visualization : Fundamentals and recent developments,” Information technology, vol. 64, Art. no. 4–5, 2022, doi: 10.1515/itit-2022-0033.

  4. 2021

    1. D. Hägele, M. A. E. Abdelaal, S. Ö. Ögüz, M. Toussaint, and D. Weiskopf, “Visual analytics for nonlinear programming in robot motion planning,” Journal of visualization, vol. 25, Art. no. 1, 2021, doi: 10.1007/s12650-021-00786-8.

  5. 2020

    1. D. Hägele, M. Abdelaal, O. S. Oguz, M. Toussaint, and D. Weiskopf, “Visualization of nonlinear programming for robot motion planning,” in Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, ACM, Dec. 2020. doi: 10.1145/3430036.3430050.

Lectures/Courses

  • Information Visualization
  • Practical Course Information Visualization
  • Programmierung für Medieninformatik (Practical Course)
  • Datenstrukturen und Algorithmen

Projects/Thesis

  • Dimensionality Reduction for Uncertain Data via Out-of-sample Extensions (Bachelor Thesis)
  • Visual Exploration for Deep Learning Models and Trainings for Microstructure Data (Master Thesis)
  • Reproducing, Extending and Updating Dimensionality Reductions (Master Thesis)
  • A Curated Collection of Multivariate Timeseries for Visualization Benchmarks (Bachelor Forschungsprojekt)
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